This study is to compare three-dimensional(3D)isotropic T2-weighted magnetic resonance imaging(MRI)with compressed sensing-sampling perfection with application optimized contrast(CS-SPACE)and the conventional image(3D...This study is to compare three-dimensional(3D)isotropic T2-weighted magnetic resonance imaging(MRI)with compressed sensing-sampling perfection with application optimized contrast(CS-SPACE)and the conventional image(3D-SPACE)sequence in terms of image quality,estimated signal-to-noise ratio(SNR),relative contrast-to-noise ratio(CNR),and the lesions’conspicuous of the female pelvis.Thirty-six females(age:51,28-73)with cervical carcinoma(n=20),rectal carcinoma(n=7),or uterine fibroid(n=9)were included.Patients underwent magnetic resonance(MR)imaging at a 3T scanner with the sequences of 3D-SPACE,CS-SPACE,and twodimensional(2D)T2-weighted turbo-spin echo(TSE).Quantitative analyses of estimated SNR and relative CNR between tumors and other tissues,image quality,and tissue conspicuity were performed.Two radiologists assessed the difference in diagnostic findings for carcinoma.Quantitative values and qualitative scores were analyzed,respectively.The estimated SNR and the relative CNR of tumor-to-muscle obturator internus,tumor-to-myometrium,and myometrium-to-muscle obturator internus was comparable between 3D-SPACE and CS-SPACE.The overall image quality and the conspicuity of the lesion scores of the CS-SPACE were higher than that of the 3D-SPACE(P<0.01).The CS-SPACE sequence offers shorter scan time,fewer artifacts,and comparable SNR and CNR to conventional 3D-SPACE,and has the potential to improve the performance of T2-weighted images.展开更多
Objective The aim of the study was to investigate the application of dynamic contrast-enhanced magnetic resonance imaging(DCE-MRI)combined with magnetic resonance spectroscopy(MRS)in prostate cancer diagnosis.Methods ...Objective The aim of the study was to investigate the application of dynamic contrast-enhanced magnetic resonance imaging(DCE-MRI)combined with magnetic resonance spectroscopy(MRS)in prostate cancer diagnosis.Methods In the outpatient department of our hospital(Sichuan Cancer Hospital,Chengdu,China),60 patients diagnosed with prostate disease were selected randomly and included in a prostate cancer group,60 patients with benign prostatic hyperplasia were included in a proliferation group,and 60 healthy subjects were included in a control group,from January 2013 to January 2017.Using Siemens Avanto 1.5 T high-field superconducting MRI for DCE-MRI and MRS scans,after the MRS scan was completed,we used the workstation spectroscopy tab spectral analysis,and eventually obtained the crest lines of the prostate metabolites choline(Cho),creatine(Cr),citrate(Cit),and the values of Cho/Cit,and(Cho+Cr)/Cit.Results Participants who had undergone 21-s,1-min,and 2-min dynamic contrast-enhanced MR revealed significant variations among the three groups.The spectral analysis of the three groups revealed a significant variation as well.DCE-MRI and MRS combined had a sensitivity of 89.67%,specificity of 95.78%,and accuracy of 94.34%.Conclusion DCE-MRI combined with MRS is of great value in the diagnosis of prostate cancer.展开更多
In recent years,utilizing the low-rank prior information to construct a signal from a small amount of measures has attracted much attention.In this paper,a generalized nonconvex low-rank(GNLR) algorithm for magnetic r...In recent years,utilizing the low-rank prior information to construct a signal from a small amount of measures has attracted much attention.In this paper,a generalized nonconvex low-rank(GNLR) algorithm for magnetic resonance imaging(MRI)reconstruction is proposed,which reconstructs the image from highly under-sampled k-space data.In the algorithm,the nonconvex surrogate function replacing the conventional nuclear norm is utilized to enhance the low-rank property inherent in the reconstructed image.An alternative direction multiplier method(ADMM) is applied to solving the resulting non-convex model.Extensive experimental results have demonstrated that the proposed method can consistently recover MRIs efficiently,and outperforms the current state-of-the-art approaches in terms of higher peak signal-to-noise ratio(PSNR) and lower high-frequency error norm(HFEN) values.展开更多
Increased interest of clinicians for using 3.0 T magnetic resonance imaging (MRI), as imaging modality of choice for their patients, has been evident in the past few years. The aim of this study was to compare the tec...Increased interest of clinicians for using 3.0 T magnetic resonance imaging (MRI), as imaging modality of choice for their patients, has been evident in the past few years. The aim of this study was to compare the technical quality of the obtained tomography using 3.0 T and 1.5 T MRI, and to compare the subjective feeling of discomfort of patients and subjective acoustic noise experience during imaging using MRI at 3.0 T and 1.5 T. Brain MRI (1.5 and 3.0 T) was performed in 58 patients, according to a standardized protocol. All studies have been randomly described by independent two radiologists. The reference standard for the existence of technical artifact is established on the basis of both radiologists’ consensus. We also compared the subjective feelings of the discomfort and acoustic noise during the both MRI (1.5 T and 3.0 T) exams. Artifacts were significantly more common during 3.0 T MRI in comparison with the 1.5 T MRI (χ2 = 5.286, P < 0.05), as well as in male patients (χ2 = 8.841, P < 0.05), and sub-jective assessments of discomfort and acoustic noise were higher in patients who underwent imaging using 3.0 T MRI, (χ2 = 125.959, df = 1, P < 0.001) and in females (χ2 = 195.449, df = 1, P < 0.001). Additional research is needed to prove that appropriate information for patients about the discomfort during 3.0 T MRI and their psychological preparation is very important element for optimal use of 3.0 T MRI in daily clinical practice.展开更多
Although 9.4 T magnetic resonance imaging(MRI) has been tested in healthy volunteers,its safety in diabetic patients is unclear.Furthermore,the effects of high static magnetic fields(SMFs),especially gradient vs.unifo...Although 9.4 T magnetic resonance imaging(MRI) has been tested in healthy volunteers,its safety in diabetic patients is unclear.Furthermore,the effects of high static magnetic fields(SMFs),especially gradient vs.uniform fields,have not been investigated in diabetics.Here,we investigated the consequences of exposure to 1.0-9.4 T high SMFs of different gradients(>10 T/m vs.0-10 T/m)on type 1 diabetic(T1D) and type 2 diabetic(T2D) mice.We found that 14 h of prolonged treatment of gradient(as high as 55.5 T/m) high SMFs(1.0-8.6 T) had negative effects on T1D and T2D mice,including spleen,hepatic,and renal tissue impairment and elevated glycosylated serum protein,blood glucose,inflammation,and anxiety,while 9.4 T quasi-uniform SMFs at 0-10 T/m did not induce the same effects.In regular T1D mice(blood glucose>16.7 mmol/L),the>10 T/m gradient high SMFs increased malondialdehyde(P<0.01) and decreased superoxide dismutase(P<0.05).However,in the severe T1D mice(blood glucose≥30.0 mmol/L),the>10 T/m gradient high SMFs significantly increased tissue damage and reduced survival rate.In vitro cellular studies showed that gradient high SMFs increased cellular reactive oxygen species and apoptosis and reduced MS-1 cell number and proliferation.Therefore,this study showed that prolonged exposure to high-field(1.0-8.6 T)>10 T/m gradient SMFs(35-1 380 times higher than that of current clinical MRI)can have negative effects on diabetic mice,especially mice with severe T1D,whereas 9.4 T high SMFs at 0-10T/m did not produce the same effects,providing important information for the future development and clinical application of SMFs,especially high-field MRI.展开更多
In this work,the authors monitored the formation and dissociation process of methane hydrate in four different rock core samples through nuclear magnetic resonance(NMR)relaxation time(T_(2))and 2D imaging measurement....In this work,the authors monitored the formation and dissociation process of methane hydrate in four different rock core samples through nuclear magnetic resonance(NMR)relaxation time(T_(2))and 2D imaging measurement.The result shows that the intensity of T_(2) spectra and magnetic resonance imaging(MRI)signals gradually decreases in the hydrate formation process,and at the same time,the T_(2) spectra move toward the left domain as the growth of hydrate in the pores of the sample accelerates the decay rate.The hydrate grows and dissociates preferentially in the purer sandstone samples with larger pore size and higher porosity.Significantly,for the sample with lower porosity and higher argillaceous content,the intensity of the T_(2) spectra also shows a trend of a great decrease in the hydrate formation process,which means that high-saturation gas hydrate can also be formed in the sample with higher argillaceous content.The changes in MRI of the sample in the process show that the formation and dissociation of methane hydrate can reshape the distribution of water in the pores.展开更多
A brain tumor is a mass of abnormal cells in the brain. Brain tumors can be benign (noncancerous) or malignant (cancerous). Conventional diagnosis of a brain tumor by the radiologist is done by examining a set of imag...A brain tumor is a mass of abnormal cells in the brain. Brain tumors can be benign (noncancerous) or malignant (cancerous). Conventional diagnosis of a brain tumor by the radiologist is done by examining a set of images produced by magnetic resonance imaging (MRI). Many computer-aided detection (CAD) systems have been developed in order to help the radiologists reach their goal of correctly classifying the MRI image. Convolutional neural networks (CNNs) have been widely used in the classification of medical images. This paper presents a novel CAD technique for the classification of brain tumors in MRI images. The proposed system extracts features from the brain MRI images by utilizing the strong energy compactness property exhibited by the Discrete Wavelet Transform (DWT). The Wavelet features are then applied to a CNN to classify the input MRI image. Experimental results indicate that the proposed approach outperforms other commonly used methods and gives an overall accuracy of 99.3%.展开更多
Objective:To investigate the CT and MRI features of salivary ductal carcinoma(SDC).Method:The imaging,clinical and pathological data of 32 patients with SDC confirmed by histomathology and operation were retrospective...Objective:To investigate the CT and MRI features of salivary ductal carcinoma(SDC).Method:The imaging,clinical and pathological data of 32 patients with SDC confirmed by histomathology and operation were retrospectively analyzed.The location,size,shape,boundary,relationship with surrounding tissues,density,signal,enhancement mode,calcification,cystic degeneration and metastasis were observed.Result:Of the 32 patients with SDC,31 cases were isolated,17 were located in the parotid gland,8 in the submandibular gland,2 in the sinuses,2 in the orbit,1 in the part of the eye,and 1 in the sublingual gland.One case had multiple lesions located in the parotid gland.The maximum diameter of tumor was 1.5-7.2cm,and the median diameter was 3.0cm.The tumor showed diffuse growth in 11 cases and focal growth in 21 cases.The boundary was clear in 24 cases and unclear in 8 cases.The lesion may invade parapharyngeal space,soft palate,facial nerve,auditory nerve,skin,surrounding muscle and bone;There were 15 cases(47%)with lymph node metastasis and 1 case with lung metastasis.MRI showed that the solid part of the tumor was dominated by isointensity and low intensity on T1 WI,mixed high intensity on T2 WI,low intensity on T1 WI and high intensity on T2 WI.CT showed uneven tumor density,with equal or low density in 15 cases,high density in 4 cases,and calcification in 7 cases.Contrast-enhanced scan showed moderate to significant enhancement of the solid part.Conclusion:SDC is mostly single,prone to cystic necrosis and calcification,with strong aggressiveness and frequent lymph node metastasis.Understanding the imaging findings of SDC is helpful to improve the accuracy of preoperative diagnosis.展开更多
Objective To present a rare case of skin allergic reaction to gadobutrol,a magnetic resonance imaging(MRI)contrast agent,in a 37-year-old man.Methods The adverse reactions of gadobutrol were analyzed combined with the...Objective To present a rare case of skin allergic reaction to gadobutrol,a magnetic resonance imaging(MRI)contrast agent,in a 37-year-old man.Methods The adverse reactions of gadobutrol were analyzed combined with the instructions and related literatures.Results and Conclusion The presence of this patient is consistent with the adverse reactions in the instructions of gadobutrol.The incidence of ADR in gadobutrol is considered to be low,although sometimes patients report a hypersensitivity reaction when undergoing MRI.There are only a few cases of immediate adverse reactions to gadobutrol.However,we should improve the ability of medical staff to use drugs safely and take preventive measures.展开更多
Magnetic resonance imaging(MRI)is a common clinical practice to visualize defects and to distinguish different tissue types and pathologies in the human body.So far,MRI data have not been used to model and generate a ...Magnetic resonance imaging(MRI)is a common clinical practice to visualize defects and to distinguish different tissue types and pathologies in the human body.So far,MRI data have not been used to model and generate a patient-specific design of multilayered tissue substitutes in the case of interfacial defects.For orthopedic cases that require highly individual surgical treatment,implant fabrication by additive manufacturing holds great potential.Extrusion-based techniques like 3D plot-ting allow the spatially defined application of several materials,as well as implementation of bioprinting strategies.With the example of a typical multi-zonal osteochondral defect in an osteochondritis dissecans(OCD)patient,this study aimed to close the technological gap between MRI analysis and the additive manufacturing process of an implant based on dif-ferent biomaterial inks.A workflow was developed which covers the processing steps of MRI-based defect identification,segmentation,modeling,implant design adjustment,and implant generation.A model implant was fabricated based on two biomaterial inks with clinically relevant properties that would allow for bioprinting,the direct embedding of a patient’s own cells in the printing process.As demonstrated by the geometric compatibility of the designed and fabricated model implant in a stereolithography(SLA)model of lesioned femoral condyles,a novel versatile CAD/CAM workflow was successfully established that opens up new perspectives for the treatment of multi-zonal(osteochondral)defects.展开更多
We describe the computed tomographic (CT) and magnetic resonance imaging (MRI) features of a very rare renal neoplasm, a glomus tumor. Our patient was a 68-year-old woman with a history of high grade T1 stage bladder ...We describe the computed tomographic (CT) and magnetic resonance imaging (MRI) features of a very rare renal neoplasm, a glomus tumor. Our patient was a 68-year-old woman with a history of high grade T1 stage bladder cancer, status post intravesical Bacillus Calmette-Guérin (BCG) therapy and left ureteral stent placement, who presented for routine follow-up imaging evaluation of the urothelial tract. Computed tomographic urography (CTU) incidentally demonstrated a 1.7 cm well-circumscribed, non-calcified, non-fat containing lesion in the left renal cortex with arterial phase continuous peripheral rim enhancement and central hypoattenuation relative to enhanced renal parenchyma. Subsequent MRI showed the lesion to be isointense in signal intensity relative to the renal parenchyma on T1-weighted imaging and hyperintense on T2-weighted imaging. No macroscopic fat or microscopic lipid was seen within the lesion, and there were no foci of susceptibility artifact on T1-weighted images. Diffusion-weighted and apparent diffusion coefficient images demonstrated no restricted diffusion. Contrast-enhanced images demonstrated continuous peripheral rim enhancement in the arterial phase and persistent rim enhancement with partial centripetal fill in of enhancement on venous phase images, similar to the pattern seen on CT. Partial left nephrectomy was performed for the suspected solid renal neoplasm. Histopathological assessment was diagnostic of a renal glomus tumor.展开更多
Objective: To evaluate the diagnostic efficacy of magnetic resonance imaging (MRI) for the detection of partial-thickness rotator cuff tears (PTT) and full-thickness rotator cuff tears(FTT) by comparing its findings w...Objective: To evaluate the diagnostic efficacy of magnetic resonance imaging (MRI) for the detection of partial-thickness rotator cuff tears (PTT) and full-thickness rotator cuff tears(FTT) by comparing its findings with surgical findings as the gold standard and to improve the previous MRI accuracy in diagnosing rotator cuff tears (RCT) considering more variables. Methods: In 45 months, 804 patients underwent MRI shoulder joint. Among them, only 95 cases had undergone both MRI imaging and surgery accordingly. The patient records were evaluated retrospectively if MRI and surgery were performed within 40 days of MRI. MRI findings were categorized into PTT, FTT and no tears which were further divided into different types according to four main nominal data as variables viz. site, size, shape and muscle involvement in RCT and were correlated with surgical findings for statistical calculation by using Kappa coefficient and McNemar Bowker test. Results: 81 patients (86 RCTs) underwent surgery within 40 days. On the basis of site as variable, MRI correctly depicted 100% of full thickness tears(FTT), 85% of bursal partial thickness tears(PTT), 80.4% of articular partial thickness tears(PTT). The consistency in diagnosis of RCT between MRI and surgery was moderate (Kappa coefficient 0.645). Overall sensitivity, specificity and accuracy of MRI for diagnosing PTT was 87.3%, 53.3% and 81.3%;and that for FTT was 100%, 98.7% and 98.8% respectively. Likewise on the basis of size, shape and muscles involved, the consistency between MRI and surgery was poor for size and shape and moderate for muscles involved;and the difference in diagnosing RCT by MRI and surgery was significant for shape (P = 0.002) only, but not significant for size (P = 0.16) and for muscles involved (P = 0.206) respectively. The agreement between MRI and surgery in diagnosing calcific tendinitis and shoulder joint hematoma with Kappa coefficient is (0.577) and (0.556) respectively. Conclusion: MRI has better accuracy for detecting FTT and has high sensitivity and positive predictive value in diagnosing both PTT and FTT. Combining more others variables in addition to RCT, MRI offers a great value in diagnosing RCT.展开更多
This review is aimed at presenting some of the recent developments in translational cancer imaging research,with a focus on novel,recently established,or soon to be established cross-sectional imaging techniques for c...This review is aimed at presenting some of the recent developments in translational cancer imaging research,with a focus on novel,recently established,or soon to be established cross-sectional imaging techniques for computed tomography(CT),magnetic resonance imaging(MRI),and positron-emission tomography(PET)imaging,including computational investigations based on machine-learning techniques.展开更多
Turner syndrome(TS)is a rare disorder affecting 25–50 in 100000 female newborns.Bicuspid aortic valve(BAV)is assumed to be the most common congenital heart defect(CHD)in TS.In literature,reported BAV prevalence in TS...Turner syndrome(TS)is a rare disorder affecting 25–50 in 100000 female newborns.Bicuspid aortic valve(BAV)is assumed to be the most common congenital heart defect(CHD)in TS.In literature,reported BAV prevalence in TS ranges between 14%and 34%.The specific BAV prevalence in TS is still unknown.The aim of this study was to give a more precise estimation of BAV prevalence in TS by conducting a meta-analysis of TS-studies,which detected BAV by either cardiac magnetic resonance imaging(MRI)or cardiac computed tomography(CT).We searched PubMed,Cochrane Library,and Web of Science databases to collect observational studies including the prevalence of BAV identified by cardiac MRI or cardiac CT in TS patients up to June 4th,2021.After screening for inclusion,data extraction,and quality assessment by two independent reviewers,the meta-analysis was performed with R 4.1.1 software.Results are shown as proportion and weighted mean difference with 95%confidence intervals(95%CI).In total,11 studies involving 1177 patients were included.Pooled data showed that the prevalence of BAV in TS patients was 23.7%(95%CI:21.3%to 26.1%).No high heterogeneity was found between the included studies.The current meta-analysis reveals that BAVcan be detected in 23.7%of TS patients receiving cardiac MRI or cardiac CT.Therefore,BAV can be considered as the most common CHD in TS.Compared to TTE,cardiac MRI and cardiac CT might represent superior imaging modalities in BAV assessment of adult TS patients.展开更多
Digital Image Processing(DIP)is a well-developed field in the biological sciences which involves classification and detection of tumour.In medical science,automatic brain tumor diagnosis is an important phase.Brain tu...Digital Image Processing(DIP)is a well-developed field in the biological sciences which involves classification and detection of tumour.In medical science,automatic brain tumor diagnosis is an important phase.Brain tumor detection is performed by Computer-Aided Diagnosis(CAD)systems.The human image creation is greatly achieved by an approach namely medical imaging which is exploited for medical and research purposes.Recently Automatic brain tumor detection from MRI images has become the emerging research area of medical research.Brain tumor diagnosis mainly performed for obtaining exact location,orientation and area of abnormal tissues.Cancer and edema regions inference from brain magnetic resonance imaging(MRI)information is considered to be great challenge due to brain tumors complex structure,blurred borders,besides exterior features like noise.The noise compassion is mainly reduced along with segmentation stability by suggesting efficient hybrid clustering method merged with morphological process for brain cancer segmentation.Combined form of Median Modified Wiener filter(CMMWF)is chiefly deployed for denoising,and morphological operations which in turn eliminate nonbrain tissue,efficiently dropping technique’s sensitivity to noise.The proposed system contains the main phases such as preprocessing,brain tumor extraction and post processing.Image segmentation is greatly achieved by presenting Intuitionist Possibilistic Fuzzy Clustering(IPFC)algorithm.The algorithm’s stability is greatly enhanced by this clustering along with clustering parameters sensitivity reduction.Then,the post processing of images are done through morphological operations along with Hybrid Median filtering(HMF)for attaining exact tumors representations.Additionally,suggested algorithm is substantiated by comparing with other existing segmentation algorithms.The outcomes reveal that suggested algorithm achieves improved outcomes pertaining to accuracy,sensitivity,specificity,and recall.展开更多
Objective: To observe the effect of multi-slice spiral CT and magnetic resonance imaging (MRI) in the diagnosis of shoulder injury. Methods: 120 patients with shoulder injury who were treated in our hospital (January ...Objective: To observe the effect of multi-slice spiral CT and magnetic resonance imaging (MRI) in the diagnosis of shoulder injury. Methods: 120 patients with shoulder injury who were treated in our hospital (January 2020 to December 2021) and underwent surgical treatment were diagnosed as shoulder injury. They were divided into CT group, MRI group and joint diagnosis group. The detection rates of the two methods were compared. Results: In the diagnosis of shoulder injury, MRI group was higher than CT group, and the joint diagnosis group was higher than the other two groups. Conclusion: In the diagnosis of shoulder injury, the joint examination of multi-slice spiral CT and magnetic resonance imaging (MRI) can obtain a higher diagnostic rate and ideal effect.展开更多
Attention mechanism combined with convolutional neural network(CNN) achieves promising performance for magnetic resonance imaging(MRI) image segmentation,however these methods only learn attention weights from single ...Attention mechanism combined with convolutional neural network(CNN) achieves promising performance for magnetic resonance imaging(MRI) image segmentation,however these methods only learn attention weights from single scale,resulting in incomplete attention learning.A novel method named completed attention convolutional neural network(CACNN) is proposed for MRI image segmentation.Specifically,the channel-wise attention block(CWAB) and the pixel-wise attention block(PWAB) are designed to learn attention weights from the aspects of channel and pixel levels.As a result,completed attention weights are obtained,which is beneficial to discriminative feature learning.The method is verified on two widely used datasets(HVSMR and MRBrainS),and the experimental results demonstrate that the proposed method achieves better results than the state-of-theart methods.展开更多
Background:Posttraumatic stress disorder(PTSD)has been associated with volumetric and white matter microstructural changes among general and veteran populations.However,regions implicated have greatly varied and often...Background:Posttraumatic stress disorder(PTSD)has been associated with volumetric and white matter microstructural changes among general and veteran populations.However,regions implicated have greatly varied and often conflict between studies,potentially due to confounding comorbidities within samples.This study compared grey matter volume and white matter microstructure among Australian combat veterans with and without a lifetime diagnosis of PTSD,in a homogenous sample assessed for known confounding comorbidities.Methods:Sixty-eight male trauma-exposed veterans(16 PTSD-diagnosed;mean age 69 years)completed a battery of psychometric assessments and underwent magnetic resonance and diffusion tensor imaging.Analyses included tractbased spatial statistics,voxel-wise analyses,diffusion connectome-based group-wise analysis,and volumetric analysis.Results:Significantly smaller grey matter volumes were observed in the left prefrontal cortex(P=0.026),bilateral middle frontal gyrus(P=0.021),and left anterior insula(P=0.048)in the PTSD group compared to controls.Significant negative correlations were found between PTSD symptom severity and fractional anisotropy values in the left corticospinal tract(R^(2)=0.34,P=0.024)and left inferior cerebellar peduncle(R^(2)=0.62,P=0.016).No connectome-based differences in white matter properties were observed.Conclusions:Findings from this study reinforce reports of white matter alterations,as indicated by reduced fractional anisotropy values,in relation to PTSD symptom severity,as well as patterns of reduced volume in the prefrontal cortex.These results contribute to the developing profile of neuroanatomical differences uniquely attributable to veterans who suffer from chronic PTSD.展开更多
Lung cancer is the leading cause of mortality in the world affectingboth men and women equally.When a radiologist just focuses on the patient’sbody, it increases the amount of strain on the radiologist and the likeli...Lung cancer is the leading cause of mortality in the world affectingboth men and women equally.When a radiologist just focuses on the patient’sbody, it increases the amount of strain on the radiologist and the likelihoodof missing pathological information such as abnormalities are increased.One of the primary objectives of this research work is to develop computerassisteddiagnosis and detection of lung cancer. It also intends to make iteasier for radiologists to identify and diagnose lung cancer accurately. Theproposed strategy which was based on a unique image feature, took intoconsideration the spatial interaction of voxels that were next to one another.Using the U-NET+Three parameter logistic distribution-based technique, wewere able to replicate the situation. The proposed technique had an averageDice co-efficient (DSC) of 97.3%, a sensitivity of 96.5% and a specificity of94.1% when tested on the Luna-16 dataset. This research investigates howdiverse lung segmentation, juxta pleural nodule inclusion, and pulmonarynodule segmentation approaches may be applied to create Computer AidedDiagnosis (CAD) systems. When we compared our approach to four otherlung segmentation methods, we discovered that ours was the most successful.We employed 40 patients from Luna-16 datasets to evaluate this. In termsof DSC performance, the findings demonstrate that the suggested techniqueoutperforms the other strategies by a significant margin.展开更多
X-Ray knee imaging is widely used to detect knee osteoarthritis due to ease of availability and lesser cost.However,the manual categorization of knee joint disorders is time-consuming,requires an expert person,and is ...X-Ray knee imaging is widely used to detect knee osteoarthritis due to ease of availability and lesser cost.However,the manual categorization of knee joint disorders is time-consuming,requires an expert person,and is costly.This article proposes a new approach to classifying knee osteoarthritis using deep learning and a whale optimization algorithm.Two pre-trained deep learning models(Efficientnet-b0 and Densenet201)have been employed for the training and feature extraction.Deep transfer learning with fixed hyperparameter values has been employed to train both selected models on the knee X-Ray images.In the next step,fusion is performed using a canonical correlation approach and obtained a feature vector that has more information than the original feature vector.After that,an improved whale optimization algorithm is developed for dimensionality reduction.The selected features are finally passed to the machine learning algorithms such as Fine-Tuned support vector machine(SVM)and neural networks for classification purposes.The experiments of the proposed framework have been conducted on the publicly available dataset and obtained the maximum accuracy of 90.1%.Also,the system is explained using Explainable Artificial Intelligence(XAI)technique called occlusion,and results are compared with recent research.Based on the results compared with recent techniques,it is shown that the proposed method’s accuracy significantly improved.展开更多
文摘This study is to compare three-dimensional(3D)isotropic T2-weighted magnetic resonance imaging(MRI)with compressed sensing-sampling perfection with application optimized contrast(CS-SPACE)and the conventional image(3D-SPACE)sequence in terms of image quality,estimated signal-to-noise ratio(SNR),relative contrast-to-noise ratio(CNR),and the lesions’conspicuous of the female pelvis.Thirty-six females(age:51,28-73)with cervical carcinoma(n=20),rectal carcinoma(n=7),or uterine fibroid(n=9)were included.Patients underwent magnetic resonance(MR)imaging at a 3T scanner with the sequences of 3D-SPACE,CS-SPACE,and twodimensional(2D)T2-weighted turbo-spin echo(TSE).Quantitative analyses of estimated SNR and relative CNR between tumors and other tissues,image quality,and tissue conspicuity were performed.Two radiologists assessed the difference in diagnostic findings for carcinoma.Quantitative values and qualitative scores were analyzed,respectively.The estimated SNR and the relative CNR of tumor-to-muscle obturator internus,tumor-to-myometrium,and myometrium-to-muscle obturator internus was comparable between 3D-SPACE and CS-SPACE.The overall image quality and the conspicuity of the lesion scores of the CS-SPACE were higher than that of the 3D-SPACE(P<0.01).The CS-SPACE sequence offers shorter scan time,fewer artifacts,and comparable SNR and CNR to conventional 3D-SPACE,and has the potential to improve the performance of T2-weighted images.
文摘Objective The aim of the study was to investigate the application of dynamic contrast-enhanced magnetic resonance imaging(DCE-MRI)combined with magnetic resonance spectroscopy(MRS)in prostate cancer diagnosis.Methods In the outpatient department of our hospital(Sichuan Cancer Hospital,Chengdu,China),60 patients diagnosed with prostate disease were selected randomly and included in a prostate cancer group,60 patients with benign prostatic hyperplasia were included in a proliferation group,and 60 healthy subjects were included in a control group,from January 2013 to January 2017.Using Siemens Avanto 1.5 T high-field superconducting MRI for DCE-MRI and MRS scans,after the MRS scan was completed,we used the workstation spectroscopy tab spectral analysis,and eventually obtained the crest lines of the prostate metabolites choline(Cho),creatine(Cr),citrate(Cit),and the values of Cho/Cit,and(Cho+Cr)/Cit.Results Participants who had undergone 21-s,1-min,and 2-min dynamic contrast-enhanced MR revealed significant variations among the three groups.The spectral analysis of the three groups revealed a significant variation as well.DCE-MRI and MRS combined had a sensitivity of 89.67%,specificity of 95.78%,and accuracy of 94.34%.Conclusion DCE-MRI combined with MRS is of great value in the diagnosis of prostate cancer.
基金National Natural Science Foundations of China(Nos.61362001,61365013,51165033)the Science and Technology Department of Jiangxi Province of China(Nos.20132BAB211030,20122BAB211015)+1 种基金the Jiangxi Advanced Projects for Postdoctoral Research Funds,China(o.2014KY02)the Innovation Special Fund Project of Nanchang University,China(o.cx2015136)
文摘In recent years,utilizing the low-rank prior information to construct a signal from a small amount of measures has attracted much attention.In this paper,a generalized nonconvex low-rank(GNLR) algorithm for magnetic resonance imaging(MRI)reconstruction is proposed,which reconstructs the image from highly under-sampled k-space data.In the algorithm,the nonconvex surrogate function replacing the conventional nuclear norm is utilized to enhance the low-rank property inherent in the reconstructed image.An alternative direction multiplier method(ADMM) is applied to solving the resulting non-convex model.Extensive experimental results have demonstrated that the proposed method can consistently recover MRIs efficiently,and outperforms the current state-of-the-art approaches in terms of higher peak signal-to-noise ratio(PSNR) and lower high-frequency error norm(HFEN) values.
文摘Increased interest of clinicians for using 3.0 T magnetic resonance imaging (MRI), as imaging modality of choice for their patients, has been evident in the past few years. The aim of this study was to compare the technical quality of the obtained tomography using 3.0 T and 1.5 T MRI, and to compare the subjective feeling of discomfort of patients and subjective acoustic noise experience during imaging using MRI at 3.0 T and 1.5 T. Brain MRI (1.5 and 3.0 T) was performed in 58 patients, according to a standardized protocol. All studies have been randomly described by independent two radiologists. The reference standard for the existence of technical artifact is established on the basis of both radiologists’ consensus. We also compared the subjective feelings of the discomfort and acoustic noise during the both MRI (1.5 T and 3.0 T) exams. Artifacts were significantly more common during 3.0 T MRI in comparison with the 1.5 T MRI (χ2 = 5.286, P < 0.05), as well as in male patients (χ2 = 8.841, P < 0.05), and sub-jective assessments of discomfort and acoustic noise were higher in patients who underwent imaging using 3.0 T MRI, (χ2 = 125.959, df = 1, P < 0.001) and in females (χ2 = 195.449, df = 1, P < 0.001). Additional research is needed to prove that appropriate information for patients about the discomfort during 3.0 T MRI and their psychological preparation is very important element for optimal use of 3.0 T MRI in daily clinical practice.
基金supported by the National Natural Science Foundation of China (U21A20148, 31900506, 52007185)International Partnership Program of the Chinese Academy of Sciences(116134KYSB20210052)+2 种基金Heye Health Technology Chong Ming Project(HYCMP2021010)CAS President’s International Fellowship Initiative Grant(2022VMA0009)CASHIPS Director’s Fund (BJPY2021A06,2021YZGH04, YZJJ2020QN26, YZJJZX202014, YZJJ2021QN32,YZJJ2023QN43)。
文摘Although 9.4 T magnetic resonance imaging(MRI) has been tested in healthy volunteers,its safety in diabetic patients is unclear.Furthermore,the effects of high static magnetic fields(SMFs),especially gradient vs.uniform fields,have not been investigated in diabetics.Here,we investigated the consequences of exposure to 1.0-9.4 T high SMFs of different gradients(>10 T/m vs.0-10 T/m)on type 1 diabetic(T1D) and type 2 diabetic(T2D) mice.We found that 14 h of prolonged treatment of gradient(as high as 55.5 T/m) high SMFs(1.0-8.6 T) had negative effects on T1D and T2D mice,including spleen,hepatic,and renal tissue impairment and elevated glycosylated serum protein,blood glucose,inflammation,and anxiety,while 9.4 T quasi-uniform SMFs at 0-10 T/m did not induce the same effects.In regular T1D mice(blood glucose>16.7 mmol/L),the>10 T/m gradient high SMFs increased malondialdehyde(P<0.01) and decreased superoxide dismutase(P<0.05).However,in the severe T1D mice(blood glucose≥30.0 mmol/L),the>10 T/m gradient high SMFs significantly increased tissue damage and reduced survival rate.In vitro cellular studies showed that gradient high SMFs increased cellular reactive oxygen species and apoptosis and reduced MS-1 cell number and proliferation.Therefore,this study showed that prolonged exposure to high-field(1.0-8.6 T)>10 T/m gradient SMFs(35-1 380 times higher than that of current clinical MRI)can have negative effects on diabetic mice,especially mice with severe T1D,whereas 9.4 T high SMFs at 0-10T/m did not produce the same effects,providing important information for the future development and clinical application of SMFs,especially high-field MRI.
基金supported by the Guangdong Province Marine Economic Development(Six Major Marine Industries)Special Fund Project([2021]56)the Key Special Project for Introduced Talents Team of Southern Marine Science and Engineering Guangdong Laboratory(Guangzhou)(GML2019ZD0105)+1 种基金the Guangzhou Science and Technology Project(202201011463)project of the China Geological Survey(DD20211350).
文摘In this work,the authors monitored the formation and dissociation process of methane hydrate in four different rock core samples through nuclear magnetic resonance(NMR)relaxation time(T_(2))and 2D imaging measurement.The result shows that the intensity of T_(2) spectra and magnetic resonance imaging(MRI)signals gradually decreases in the hydrate formation process,and at the same time,the T_(2) spectra move toward the left domain as the growth of hydrate in the pores of the sample accelerates the decay rate.The hydrate grows and dissociates preferentially in the purer sandstone samples with larger pore size and higher porosity.Significantly,for the sample with lower porosity and higher argillaceous content,the intensity of the T_(2) spectra also shows a trend of a great decrease in the hydrate formation process,which means that high-saturation gas hydrate can also be formed in the sample with higher argillaceous content.The changes in MRI of the sample in the process show that the formation and dissociation of methane hydrate can reshape the distribution of water in the pores.
文摘A brain tumor is a mass of abnormal cells in the brain. Brain tumors can be benign (noncancerous) or malignant (cancerous). Conventional diagnosis of a brain tumor by the radiologist is done by examining a set of images produced by magnetic resonance imaging (MRI). Many computer-aided detection (CAD) systems have been developed in order to help the radiologists reach their goal of correctly classifying the MRI image. Convolutional neural networks (CNNs) have been widely used in the classification of medical images. This paper presents a novel CAD technique for the classification of brain tumors in MRI images. The proposed system extracts features from the brain MRI images by utilizing the strong energy compactness property exhibited by the Discrete Wavelet Transform (DWT). The Wavelet features are then applied to a CNN to classify the input MRI image. Experimental results indicate that the proposed approach outperforms other commonly used methods and gives an overall accuracy of 99.3%.
文摘Objective:To investigate the CT and MRI features of salivary ductal carcinoma(SDC).Method:The imaging,clinical and pathological data of 32 patients with SDC confirmed by histomathology and operation were retrospectively analyzed.The location,size,shape,boundary,relationship with surrounding tissues,density,signal,enhancement mode,calcification,cystic degeneration and metastasis were observed.Result:Of the 32 patients with SDC,31 cases were isolated,17 were located in the parotid gland,8 in the submandibular gland,2 in the sinuses,2 in the orbit,1 in the part of the eye,and 1 in the sublingual gland.One case had multiple lesions located in the parotid gland.The maximum diameter of tumor was 1.5-7.2cm,and the median diameter was 3.0cm.The tumor showed diffuse growth in 11 cases and focal growth in 21 cases.The boundary was clear in 24 cases and unclear in 8 cases.The lesion may invade parapharyngeal space,soft palate,facial nerve,auditory nerve,skin,surrounding muscle and bone;There were 15 cases(47%)with lymph node metastasis and 1 case with lung metastasis.MRI showed that the solid part of the tumor was dominated by isointensity and low intensity on T1 WI,mixed high intensity on T2 WI,low intensity on T1 WI and high intensity on T2 WI.CT showed uneven tumor density,with equal or low density in 15 cases,high density in 4 cases,and calcification in 7 cases.Contrast-enhanced scan showed moderate to significant enhancement of the solid part.Conclusion:SDC is mostly single,prone to cystic necrosis and calcification,with strong aggressiveness and frequent lymph node metastasis.Understanding the imaging findings of SDC is helpful to improve the accuracy of preoperative diagnosis.
文摘Objective To present a rare case of skin allergic reaction to gadobutrol,a magnetic resonance imaging(MRI)contrast agent,in a 37-year-old man.Methods The adverse reactions of gadobutrol were analyzed combined with the instructions and related literatures.Results and Conclusion The presence of this patient is consistent with the adverse reactions in the instructions of gadobutrol.The incidence of ADR in gadobutrol is considered to be low,although sometimes patients report a hypersensitivity reaction when undergoing MRI.There are only a few cases of immediate adverse reactions to gadobutrol.However,we should improve the ability of medical staff to use drugs safely and take preventive measures.
基金Open Access funding enabled and organized by Projekt DEAL.
文摘Magnetic resonance imaging(MRI)is a common clinical practice to visualize defects and to distinguish different tissue types and pathologies in the human body.So far,MRI data have not been used to model and generate a patient-specific design of multilayered tissue substitutes in the case of interfacial defects.For orthopedic cases that require highly individual surgical treatment,implant fabrication by additive manufacturing holds great potential.Extrusion-based techniques like 3D plot-ting allow the spatially defined application of several materials,as well as implementation of bioprinting strategies.With the example of a typical multi-zonal osteochondral defect in an osteochondritis dissecans(OCD)patient,this study aimed to close the technological gap between MRI analysis and the additive manufacturing process of an implant based on dif-ferent biomaterial inks.A workflow was developed which covers the processing steps of MRI-based defect identification,segmentation,modeling,implant design adjustment,and implant generation.A model implant was fabricated based on two biomaterial inks with clinically relevant properties that would allow for bioprinting,the direct embedding of a patient’s own cells in the printing process.As demonstrated by the geometric compatibility of the designed and fabricated model implant in a stereolithography(SLA)model of lesioned femoral condyles,a novel versatile CAD/CAM workflow was successfully established that opens up new perspectives for the treatment of multi-zonal(osteochondral)defects.
文摘We describe the computed tomographic (CT) and magnetic resonance imaging (MRI) features of a very rare renal neoplasm, a glomus tumor. Our patient was a 68-year-old woman with a history of high grade T1 stage bladder cancer, status post intravesical Bacillus Calmette-Guérin (BCG) therapy and left ureteral stent placement, who presented for routine follow-up imaging evaluation of the urothelial tract. Computed tomographic urography (CTU) incidentally demonstrated a 1.7 cm well-circumscribed, non-calcified, non-fat containing lesion in the left renal cortex with arterial phase continuous peripheral rim enhancement and central hypoattenuation relative to enhanced renal parenchyma. Subsequent MRI showed the lesion to be isointense in signal intensity relative to the renal parenchyma on T1-weighted imaging and hyperintense on T2-weighted imaging. No macroscopic fat or microscopic lipid was seen within the lesion, and there were no foci of susceptibility artifact on T1-weighted images. Diffusion-weighted and apparent diffusion coefficient images demonstrated no restricted diffusion. Contrast-enhanced images demonstrated continuous peripheral rim enhancement in the arterial phase and persistent rim enhancement with partial centripetal fill in of enhancement on venous phase images, similar to the pattern seen on CT. Partial left nephrectomy was performed for the suspected solid renal neoplasm. Histopathological assessment was diagnostic of a renal glomus tumor.
文摘Objective: To evaluate the diagnostic efficacy of magnetic resonance imaging (MRI) for the detection of partial-thickness rotator cuff tears (PTT) and full-thickness rotator cuff tears(FTT) by comparing its findings with surgical findings as the gold standard and to improve the previous MRI accuracy in diagnosing rotator cuff tears (RCT) considering more variables. Methods: In 45 months, 804 patients underwent MRI shoulder joint. Among them, only 95 cases had undergone both MRI imaging and surgery accordingly. The patient records were evaluated retrospectively if MRI and surgery were performed within 40 days of MRI. MRI findings were categorized into PTT, FTT and no tears which were further divided into different types according to four main nominal data as variables viz. site, size, shape and muscle involvement in RCT and were correlated with surgical findings for statistical calculation by using Kappa coefficient and McNemar Bowker test. Results: 81 patients (86 RCTs) underwent surgery within 40 days. On the basis of site as variable, MRI correctly depicted 100% of full thickness tears(FTT), 85% of bursal partial thickness tears(PTT), 80.4% of articular partial thickness tears(PTT). The consistency in diagnosis of RCT between MRI and surgery was moderate (Kappa coefficient 0.645). Overall sensitivity, specificity and accuracy of MRI for diagnosing PTT was 87.3%, 53.3% and 81.3%;and that for FTT was 100%, 98.7% and 98.8% respectively. Likewise on the basis of size, shape and muscles involved, the consistency between MRI and surgery was poor for size and shape and moderate for muscles involved;and the difference in diagnosing RCT by MRI and surgery was significant for shape (P = 0.002) only, but not significant for size (P = 0.16) and for muscles involved (P = 0.206) respectively. The agreement between MRI and surgery in diagnosing calcific tendinitis and shoulder joint hematoma with Kappa coefficient is (0.577) and (0.556) respectively. Conclusion: MRI has better accuracy for detecting FTT and has high sensitivity and positive predictive value in diagnosing both PTT and FTT. Combining more others variables in addition to RCT, MRI offers a great value in diagnosing RCT.
文摘This review is aimed at presenting some of the recent developments in translational cancer imaging research,with a focus on novel,recently established,or soon to be established cross-sectional imaging techniques for computed tomography(CT),magnetic resonance imaging(MRI),and positron-emission tomography(PET)imaging,including computational investigations based on machine-learning techniques.
文摘Turner syndrome(TS)is a rare disorder affecting 25–50 in 100000 female newborns.Bicuspid aortic valve(BAV)is assumed to be the most common congenital heart defect(CHD)in TS.In literature,reported BAV prevalence in TS ranges between 14%and 34%.The specific BAV prevalence in TS is still unknown.The aim of this study was to give a more precise estimation of BAV prevalence in TS by conducting a meta-analysis of TS-studies,which detected BAV by either cardiac magnetic resonance imaging(MRI)or cardiac computed tomography(CT).We searched PubMed,Cochrane Library,and Web of Science databases to collect observational studies including the prevalence of BAV identified by cardiac MRI or cardiac CT in TS patients up to June 4th,2021.After screening for inclusion,data extraction,and quality assessment by two independent reviewers,the meta-analysis was performed with R 4.1.1 software.Results are shown as proportion and weighted mean difference with 95%confidence intervals(95%CI).In total,11 studies involving 1177 patients were included.Pooled data showed that the prevalence of BAV in TS patients was 23.7%(95%CI:21.3%to 26.1%).No high heterogeneity was found between the included studies.The current meta-analysis reveals that BAVcan be detected in 23.7%of TS patients receiving cardiac MRI or cardiac CT.Therefore,BAV can be considered as the most common CHD in TS.Compared to TTE,cardiac MRI and cardiac CT might represent superior imaging modalities in BAV assessment of adult TS patients.
文摘Digital Image Processing(DIP)is a well-developed field in the biological sciences which involves classification and detection of tumour.In medical science,automatic brain tumor diagnosis is an important phase.Brain tumor detection is performed by Computer-Aided Diagnosis(CAD)systems.The human image creation is greatly achieved by an approach namely medical imaging which is exploited for medical and research purposes.Recently Automatic brain tumor detection from MRI images has become the emerging research area of medical research.Brain tumor diagnosis mainly performed for obtaining exact location,orientation and area of abnormal tissues.Cancer and edema regions inference from brain magnetic resonance imaging(MRI)information is considered to be great challenge due to brain tumors complex structure,blurred borders,besides exterior features like noise.The noise compassion is mainly reduced along with segmentation stability by suggesting efficient hybrid clustering method merged with morphological process for brain cancer segmentation.Combined form of Median Modified Wiener filter(CMMWF)is chiefly deployed for denoising,and morphological operations which in turn eliminate nonbrain tissue,efficiently dropping technique’s sensitivity to noise.The proposed system contains the main phases such as preprocessing,brain tumor extraction and post processing.Image segmentation is greatly achieved by presenting Intuitionist Possibilistic Fuzzy Clustering(IPFC)algorithm.The algorithm’s stability is greatly enhanced by this clustering along with clustering parameters sensitivity reduction.Then,the post processing of images are done through morphological operations along with Hybrid Median filtering(HMF)for attaining exact tumors representations.Additionally,suggested algorithm is substantiated by comparing with other existing segmentation algorithms.The outcomes reveal that suggested algorithm achieves improved outcomes pertaining to accuracy,sensitivity,specificity,and recall.
文摘Objective: To observe the effect of multi-slice spiral CT and magnetic resonance imaging (MRI) in the diagnosis of shoulder injury. Methods: 120 patients with shoulder injury who were treated in our hospital (January 2020 to December 2021) and underwent surgical treatment were diagnosed as shoulder injury. They were divided into CT group, MRI group and joint diagnosis group. The detection rates of the two methods were compared. Results: In the diagnosis of shoulder injury, MRI group was higher than CT group, and the joint diagnosis group was higher than the other two groups. Conclusion: In the diagnosis of shoulder injury, the joint examination of multi-slice spiral CT and magnetic resonance imaging (MRI) can obtain a higher diagnostic rate and ideal effect.
基金Supported National Natural Science Foundation of China (No.62171321)Tianjin Municipal Natural Science Foundation (No.20JCZDJC00180,19 JCZDJC31500)the Open Projects Program of National Laboratory of Pattern Recognition (No.202000002)。
文摘Attention mechanism combined with convolutional neural network(CNN) achieves promising performance for magnetic resonance imaging(MRI) image segmentation,however these methods only learn attention weights from single scale,resulting in incomplete attention learning.A novel method named completed attention convolutional neural network(CACNN) is proposed for MRI image segmentation.Specifically,the channel-wise attention block(CWAB) and the pixel-wise attention block(PWAB) are designed to learn attention weights from the aspects of channel and pixel levels.As a result,completed attention weights are obtained,which is beneficial to discriminative feature learning.The method is verified on two widely used datasets(HVSMR and MRBrainS),and the experimental results demonstrate that the proposed method achieves better results than the state-of-theart methods.
基金RSL Queensland funded this study as part of the PTSD Initiative at the Gallipoli Medical Research Foundation.The Australian Government Department of Veterans’Affairs provided transport for eligible participants。
文摘Background:Posttraumatic stress disorder(PTSD)has been associated with volumetric and white matter microstructural changes among general and veteran populations.However,regions implicated have greatly varied and often conflict between studies,potentially due to confounding comorbidities within samples.This study compared grey matter volume and white matter microstructure among Australian combat veterans with and without a lifetime diagnosis of PTSD,in a homogenous sample assessed for known confounding comorbidities.Methods:Sixty-eight male trauma-exposed veterans(16 PTSD-diagnosed;mean age 69 years)completed a battery of psychometric assessments and underwent magnetic resonance and diffusion tensor imaging.Analyses included tractbased spatial statistics,voxel-wise analyses,diffusion connectome-based group-wise analysis,and volumetric analysis.Results:Significantly smaller grey matter volumes were observed in the left prefrontal cortex(P=0.026),bilateral middle frontal gyrus(P=0.021),and left anterior insula(P=0.048)in the PTSD group compared to controls.Significant negative correlations were found between PTSD symptom severity and fractional anisotropy values in the left corticospinal tract(R^(2)=0.34,P=0.024)and left inferior cerebellar peduncle(R^(2)=0.62,P=0.016).No connectome-based differences in white matter properties were observed.Conclusions:Findings from this study reinforce reports of white matter alterations,as indicated by reduced fractional anisotropy values,in relation to PTSD symptom severity,as well as patterns of reduced volume in the prefrontal cortex.These results contribute to the developing profile of neuroanatomical differences uniquely attributable to veterans who suffer from chronic PTSD.
基金supported by the Ministry of SMEs and Startups (MSS),Korea,under the“Startup growth technology development program (R&D,S3125114)”by the Ministry of Small and Medium-sized Enterprises (SMEs)and Startups (MSS),Korea,under the“Regional Specialized Industry Development Plus Program (R&D,S3246057)”supervised by the Korea Institute for Advancement of Technology (KIAT).
文摘Lung cancer is the leading cause of mortality in the world affectingboth men and women equally.When a radiologist just focuses on the patient’sbody, it increases the amount of strain on the radiologist and the likelihoodof missing pathological information such as abnormalities are increased.One of the primary objectives of this research work is to develop computerassisteddiagnosis and detection of lung cancer. It also intends to make iteasier for radiologists to identify and diagnose lung cancer accurately. Theproposed strategy which was based on a unique image feature, took intoconsideration the spatial interaction of voxels that were next to one another.Using the U-NET+Three parameter logistic distribution-based technique, wewere able to replicate the situation. The proposed technique had an averageDice co-efficient (DSC) of 97.3%, a sensitivity of 96.5% and a specificity of94.1% when tested on the Luna-16 dataset. This research investigates howdiverse lung segmentation, juxta pleural nodule inclusion, and pulmonarynodule segmentation approaches may be applied to create Computer AidedDiagnosis (CAD) systems. When we compared our approach to four otherlung segmentation methods, we discovered that ours was the most successful.We employed 40 patients from Luna-16 datasets to evaluate this. In termsof DSC performance, the findings demonstrate that the suggested techniqueoutperforms the other strategies by a significant margin.
基金supported by“Human Resources Program in Energy Technology”of the Korea Institute of Energy Technology Evaluation and Planning (KETEP),granted financial resources from the Ministry of Trade,Industry&Energy,Republic of Korea.(No.20204010600090).
文摘X-Ray knee imaging is widely used to detect knee osteoarthritis due to ease of availability and lesser cost.However,the manual categorization of knee joint disorders is time-consuming,requires an expert person,and is costly.This article proposes a new approach to classifying knee osteoarthritis using deep learning and a whale optimization algorithm.Two pre-trained deep learning models(Efficientnet-b0 and Densenet201)have been employed for the training and feature extraction.Deep transfer learning with fixed hyperparameter values has been employed to train both selected models on the knee X-Ray images.In the next step,fusion is performed using a canonical correlation approach and obtained a feature vector that has more information than the original feature vector.After that,an improved whale optimization algorithm is developed for dimensionality reduction.The selected features are finally passed to the machine learning algorithms such as Fine-Tuned support vector machine(SVM)and neural networks for classification purposes.The experiments of the proposed framework have been conducted on the publicly available dataset and obtained the maximum accuracy of 90.1%.Also,the system is explained using Explainable Artificial Intelligence(XAI)technique called occlusion,and results are compared with recent research.Based on the results compared with recent techniques,it is shown that the proposed method’s accuracy significantly improved.
