AIM: To establish a computed tomography (CT)-morphological classification for hepatic alveolar echinococcosis was the aim of the study.METHODS: The CT morphology of hepatic lesions in 228 patients with confirmed alveo...AIM: To establish a computed tomography (CT)-morphological classification for hepatic alveolar echinococcosis was the aim of the study.METHODS: The CT morphology of hepatic lesions in 228 patients with confirmed alveolar echinococcosis (AE) drawn from the Echinococcus Databank of the University Hospital of Ulm was reviewed retrospectively. For this reason, CT datasets of combined positron emission tomography (PET)-CT examinations were evaluated. The diagnosis of AE was made in patients with unequivocal seropositivity; positive histological findings following diagnostic puncture or partial resection of the liver; and/or findings typical for AE at either ultrasonography, CT, magnetic resonance imaging or PET-CT. The CT-morphological findings were grouped into the new classification scheme.RESULTS: Within the classification a lesion was dedicated to one out of five “primary morphologies” as well as to one out of six “patterns of calcification”. “primary morphology” and “pattern of calcification” are primarily focussed on separately from each other and combined, whereas the “primary morphology” V is not further characterized by a “pattern of calcification”. Based on the five primary morphologies, further descriptive sub-criteria were appended to types I-III. An analysis of the calcification pattern in relation to the primary morphology revealed the exclusive association of the central calcification with type IV primary morphology. Similarly, certain calcification patterns exhibited a clear predominance for other primary morphologies, which underscores the delimitation of the individual primary morphological types from each other. These relationships in terms of calcification patterns extend into the primary morphological sub-criteria, demonstrating the clear subordination of those criteria.CONCLUSION: The proposed CT-morphological classification (EMUC-CT) is intended to facilitate the recognition and interpretation of lesions in hepatic alveolar echinococcosis. This could help to interpret different clinical courses better and shall assist in the context of scientific studies to improve the comparability of CT findings.展开更多
Recently,automatic diagnosis of diabetic retinopathy(DR)from the retinal image is the most significant ressearch topic in the medical applications.Diabetic macular edema(DME)is the.major reason for the loss of vision ...Recently,automatic diagnosis of diabetic retinopathy(DR)from the retinal image is the most significant ressearch topic in the medical applications.Diabetic macular edema(DME)is the.major reason for the loss of vision in patients suffering fom DR.Early identification of the DR enables to prevent the vision loss and encourage diabetic control activities.Many techniques are.developed to diagnose the DR.The major drawbacks of the existing techniques are low accuracy and high time complexity.To owercome these issues,this paper propases an enhanced particle swarm optimization differential evolution feature selection(PSO DEFS)based feature selection approach with biometric aut hentication for the identification of DR.Initially,a hybrid median filter(HMF)is used for pre processing the input images.Then,the pre-processed images are embedded with each other by using least significant bit(LSB)for authentication purpose.Si-multaneously,the image features are extracted using convoluted local tetra pattern(CLTrP)and Tamura features.Feature selection is performed using PSO DEFS and PSO-gravitational search algorithm(PSO GSA)to reduce time complexity.Based on some performance metrics,the PSO-DEFS is chosen as a better choice for feature selection.The feature selection is performed based on the fitness value.A multi-relevance vector machine(M-RVM)is introduced to dlassify the 13 normal and 62 abnormal images among 75 images from 60 patients.Finally,the DR patients are further dassified by M-RVM.The experimental results exhibit that the proposed approach achieves better accuracy,sensitivity,and specificity than the exist ing techniques.展开更多
文摘AIM: To establish a computed tomography (CT)-morphological classification for hepatic alveolar echinococcosis was the aim of the study.METHODS: The CT morphology of hepatic lesions in 228 patients with confirmed alveolar echinococcosis (AE) drawn from the Echinococcus Databank of the University Hospital of Ulm was reviewed retrospectively. For this reason, CT datasets of combined positron emission tomography (PET)-CT examinations were evaluated. The diagnosis of AE was made in patients with unequivocal seropositivity; positive histological findings following diagnostic puncture or partial resection of the liver; and/or findings typical for AE at either ultrasonography, CT, magnetic resonance imaging or PET-CT. The CT-morphological findings were grouped into the new classification scheme.RESULTS: Within the classification a lesion was dedicated to one out of five “primary morphologies” as well as to one out of six “patterns of calcification”. “primary morphology” and “pattern of calcification” are primarily focussed on separately from each other and combined, whereas the “primary morphology” V is not further characterized by a “pattern of calcification”. Based on the five primary morphologies, further descriptive sub-criteria were appended to types I-III. An analysis of the calcification pattern in relation to the primary morphology revealed the exclusive association of the central calcification with type IV primary morphology. Similarly, certain calcification patterns exhibited a clear predominance for other primary morphologies, which underscores the delimitation of the individual primary morphological types from each other. These relationships in terms of calcification patterns extend into the primary morphological sub-criteria, demonstrating the clear subordination of those criteria.CONCLUSION: The proposed CT-morphological classification (EMUC-CT) is intended to facilitate the recognition and interpretation of lesions in hepatic alveolar echinococcosis. This could help to interpret different clinical courses better and shall assist in the context of scientific studies to improve the comparability of CT findings.
文摘Recently,automatic diagnosis of diabetic retinopathy(DR)from the retinal image is the most significant ressearch topic in the medical applications.Diabetic macular edema(DME)is the.major reason for the loss of vision in patients suffering fom DR.Early identification of the DR enables to prevent the vision loss and encourage diabetic control activities.Many techniques are.developed to diagnose the DR.The major drawbacks of the existing techniques are low accuracy and high time complexity.To owercome these issues,this paper propases an enhanced particle swarm optimization differential evolution feature selection(PSO DEFS)based feature selection approach with biometric aut hentication for the identification of DR.Initially,a hybrid median filter(HMF)is used for pre processing the input images.Then,the pre-processed images are embedded with each other by using least significant bit(LSB)for authentication purpose.Si-multaneously,the image features are extracted using convoluted local tetra pattern(CLTrP)and Tamura features.Feature selection is performed using PSO DEFS and PSO-gravitational search algorithm(PSO GSA)to reduce time complexity.Based on some performance metrics,the PSO-DEFS is chosen as a better choice for feature selection.The feature selection is performed based on the fitness value.A multi-relevance vector machine(M-RVM)is introduced to dlassify the 13 normal and 62 abnormal images among 75 images from 60 patients.Finally,the DR patients are further dassified by M-RVM.The experimental results exhibit that the proposed approach achieves better accuracy,sensitivity,and specificity than the exist ing techniques.
