BACKGROUND Acute fibroid complications are rare.However,failure to recognize and treat acute complications expeditiously when they occur can lead to catastrophic,even deadly,complications.Pyomyoma is a rare but potent...BACKGROUND Acute fibroid complications are rare.However,failure to recognize and treat acute complications expeditiously when they occur can lead to catastrophic,even deadly,complications.Pyomyoma is a rare but potentially fatal condition resulting from infarction and infection of a fibroid through bacterial seeding and direct,hematogenous,or lymphatic dissemination.Even though the diagnosis is established through clinical and laboratory findings,imaging is an important complementary method to support the suspected diagnosis.CASE SUMMARY Herein,we report a case of a pyomyoma in a nulliparous woman previously diagnosed with uterine leiomyomatosis according to ultrasound findings.The patient had previously attended the emergency room due to hypogastric pain unresponsive to analgesics.After a week of persistent pain,she developed sepsis without any identifiable foci.Magnetic resonance imaging revealed findings compatible with uterine myomatosis with red degeneration,and a possible diagnosis of a pyomyoma was made according to the imaging findings along with the patient’s clinical features.We decided to perform myomectomy(which is an infrequently performed surgical treatment due to the procedure’s intrinsic implic-ations)due to the patient’s desire to preserve fertility.Histopathologic results revealed a uterine leiomyoma with coagulative and liquefactive necrosis,while the tissue culture showed gram-negative cocci bacteria,which were successfully treated using antibiotic therapy.The patient’s health status improved after several days.CONCLUSION The main diagnostic tools to evaluate pyomyomas are the clinical and laboratory findings as well as tissue cultures.Nonetheless,magnetic resonance imaging can help to corroborate these findings as well as to better characterize myomas with its different complications.展开更多
This document presents a computer vision system for the automatic recognition of Mexican Sign Language (MSL), based on normalized moments as invariant (to translation and scale transforms) descriptors, using artificia...This document presents a computer vision system for the automatic recognition of Mexican Sign Language (MSL), based on normalized moments as invariant (to translation and scale transforms) descriptors, using artificial neural networks as pattern recognition model. An experimental feature selection was performed to reduce computational costs due to this work focusing on automatic recognition. The computer vision system includes four LED-reflectors of 700 lumens each in order to improve image acquisition quality;this illumination system allows reducing shadows in each sign of the MSL. MSL contains 27 signs in total but 6 of them are expressed with movement;this paper presents a framework for the automatic recognition of 21 static signs of MSL. The proposed system achieved 93% of recognition rate.展开更多
The present work introduces a system for recognizing static signs in Mexican Sign Language (MSL) using Jacobi-Fourier Moments (JFMs) and Artificial Neural Networks (ANN). The original color images of static signs are ...The present work introduces a system for recognizing static signs in Mexican Sign Language (MSL) using Jacobi-Fourier Moments (JFMs) and Artificial Neural Networks (ANN). The original color images of static signs are cropped, segmented and converted to grayscale. Then to reduce computational costs 64 JFMs were calculated to represent each image. The JFMs are sorted to select a subset that improves recognition according to a metric proposed by us based on a ratio between dispersion measures. Using WEKA software to test a Multilayer-Perceptron with this subset of JFMs reached 95% of recognition rate.展开更多
文摘BACKGROUND Acute fibroid complications are rare.However,failure to recognize and treat acute complications expeditiously when they occur can lead to catastrophic,even deadly,complications.Pyomyoma is a rare but potentially fatal condition resulting from infarction and infection of a fibroid through bacterial seeding and direct,hematogenous,or lymphatic dissemination.Even though the diagnosis is established through clinical and laboratory findings,imaging is an important complementary method to support the suspected diagnosis.CASE SUMMARY Herein,we report a case of a pyomyoma in a nulliparous woman previously diagnosed with uterine leiomyomatosis according to ultrasound findings.The patient had previously attended the emergency room due to hypogastric pain unresponsive to analgesics.After a week of persistent pain,she developed sepsis without any identifiable foci.Magnetic resonance imaging revealed findings compatible with uterine myomatosis with red degeneration,and a possible diagnosis of a pyomyoma was made according to the imaging findings along with the patient’s clinical features.We decided to perform myomectomy(which is an infrequently performed surgical treatment due to the procedure’s intrinsic implic-ations)due to the patient’s desire to preserve fertility.Histopathologic results revealed a uterine leiomyoma with coagulative and liquefactive necrosis,while the tissue culture showed gram-negative cocci bacteria,which were successfully treated using antibiotic therapy.The patient’s health status improved after several days.CONCLUSION The main diagnostic tools to evaluate pyomyomas are the clinical and laboratory findings as well as tissue cultures.Nonetheless,magnetic resonance imaging can help to corroborate these findings as well as to better characterize myomas with its different complications.
文摘This document presents a computer vision system for the automatic recognition of Mexican Sign Language (MSL), based on normalized moments as invariant (to translation and scale transforms) descriptors, using artificial neural networks as pattern recognition model. An experimental feature selection was performed to reduce computational costs due to this work focusing on automatic recognition. The computer vision system includes four LED-reflectors of 700 lumens each in order to improve image acquisition quality;this illumination system allows reducing shadows in each sign of the MSL. MSL contains 27 signs in total but 6 of them are expressed with movement;this paper presents a framework for the automatic recognition of 21 static signs of MSL. The proposed system achieved 93% of recognition rate.
文摘The present work introduces a system for recognizing static signs in Mexican Sign Language (MSL) using Jacobi-Fourier Moments (JFMs) and Artificial Neural Networks (ANN). The original color images of static signs are cropped, segmented and converted to grayscale. Then to reduce computational costs 64 JFMs were calculated to represent each image. The JFMs are sorted to select a subset that improves recognition according to a metric proposed by us based on a ratio between dispersion measures. Using WEKA software to test a Multilayer-Perceptron with this subset of JFMs reached 95% of recognition rate.
