Brain cancer is the premier reason for cancer deaths all over the world.The diagnosis of brain cancer at an initial stage is mediocre,as the radiologist is ineffectual.Different experiments have been conducted and dem...Brain cancer is the premier reason for cancer deaths all over the world.The diagnosis of brain cancer at an initial stage is mediocre,as the radiologist is ineffectual.Different experiments have been conducted and demonstrated clearly that the algorithms for nodule segmentation are unsuccessful.Therefore,the research has consolidated incremental clustering focused on superpixel segmentation as an appropriate optimization approach for the accurate segmentation of pulmonary nodules.The key aim of the research is to refine brain CT images to accurately distinguish tumors and the segmentation of small-scale anomalous nodules in the brain region.In the beginning stage,an anisotropic diffusion filters(ADF)method with un-sharp intensification masking is utilized to eliminate the noise discernment in images.In the following stage,within the improved nodule image sequence,a Superpixel Segmentation Based Iterative Clustering(SSBIC)algorithm is proposed for irregular brain tissue prediction.Subsequently,the brain nodule samples are captured using deep learning methods:Advanced Grey Wolf Optimization(AGWO)with ONN(AGWO-ONN)and Advanced GWO with CNN-based(AGWOCNN).The proposed technique indicates that the sensitivity is increased and the calculation time is decreased.Consequently,the proposed methodology manifests that the advanced Computer-Assisted Diagnosis(CAD)system has outstanding potential for automatic brain tumor diagnosis.The average segmentation time of the nodule slice order is 1.06s,and 97%of AGWO-ONN and 97.6%of AGWO-CNN achieve the best classification reliability.展开更多
Continuous phase plate（CPP）,which has a function of beam shaping in laser systems,is one kind of important diffractive optics.Based on the Fourier transform of the Gerchberg-Saxton（G-S） algorithm for designing CPP...Continuous phase plate（CPP）,which has a function of beam shaping in laser systems,is one kind of important diffractive optics.Based on the Fourier transform of the Gerchberg-Saxton（G-S） algorithm for designing CPP,we proposed an optical diffraction method according to the real system conditions.A thin lens can complete the Fourier transform of the input signal and the inverse propagation of light can be implemented in a program.Using both of the two functions can realize the iteration process to calculate the near-field distribution of light and the far-field repeatedly,which is similar to the G-S algorithm.The results show that using the optical diffraction method can design a CPP for a complicated laser system,and make the CPP have abilities of beam shaping and phase compensation for the phase aberration of the system.The method can improve the adaptation of the phase plate in systems with phase aberrations.展开更多
文摘Brain cancer is the premier reason for cancer deaths all over the world.The diagnosis of brain cancer at an initial stage is mediocre,as the radiologist is ineffectual.Different experiments have been conducted and demonstrated clearly that the algorithms for nodule segmentation are unsuccessful.Therefore,the research has consolidated incremental clustering focused on superpixel segmentation as an appropriate optimization approach for the accurate segmentation of pulmonary nodules.The key aim of the research is to refine brain CT images to accurately distinguish tumors and the segmentation of small-scale anomalous nodules in the brain region.In the beginning stage,an anisotropic diffusion filters(ADF)method with un-sharp intensification masking is utilized to eliminate the noise discernment in images.In the following stage,within the improved nodule image sequence,a Superpixel Segmentation Based Iterative Clustering(SSBIC)algorithm is proposed for irregular brain tissue prediction.Subsequently,the brain nodule samples are captured using deep learning methods:Advanced Grey Wolf Optimization(AGWO)with ONN(AGWO-ONN)and Advanced GWO with CNN-based(AGWOCNN).The proposed technique indicates that the sensitivity is increased and the calculation time is decreased.Consequently,the proposed methodology manifests that the advanced Computer-Assisted Diagnosis(CAD)system has outstanding potential for automatic brain tumor diagnosis.The average segmentation time of the nodule slice order is 1.06s,and 97%of AGWO-ONN and 97.6%of AGWO-CNN achieve the best classification reliability.
文摘Continuous phase plate（CPP）,which has a function of beam shaping in laser systems,is one kind of important diffractive optics.Based on the Fourier transform of the Gerchberg-Saxton（G-S） algorithm for designing CPP,we proposed an optical diffraction method according to the real system conditions.A thin lens can complete the Fourier transform of the input signal and the inverse propagation of light can be implemented in a program.Using both of the two functions can realize the iteration process to calculate the near-field distribution of light and the far-field repeatedly,which is similar to the G-S algorithm.The results show that using the optical diffraction method can design a CPP for a complicated laser system,and make the CPP have abilities of beam shaping and phase compensation for the phase aberration of the system.The method can improve the adaptation of the phase plate in systems with phase aberrations.
