We present a case of left ectopic ureter insertion into the left seminal vesicle which is a rare anomaly.The incidence of ectopic insertion of the ureter is more common in females and is usually associated with incont...We present a case of left ectopic ureter insertion into the left seminal vesicle which is a rare anomaly.The incidence of ectopic insertion of the ureter is more common in females and is usually associated with incontinence,leading to the diagnosis,while in males it is present with infection.Ectopic ureter is defined as abnormal insertion of the ureter,occurring in the posterior urethra in approximately 50%of cases in males.Other sites include the seminal vesicle(approximately one-third),vas deferens,bladder neck,prostate and epididymis,while the urethra and vagina are commonly affected in females.Management is usually addressed to the upper tract only;if there is incontinence it requires removal of the ureteric stump.Our case was initially diagnosed by magnetic resonance imaging and the diagnosis confirmed by computed tomography(CT)guided seminal vesiculography as transrectal guidance for seminal vesiculography was refused by the patient.CT guided seminal vesiculography is less painful and more tolerable than the transrectal route.展开更多
A new framework for early diagnosis of prostate cancer using Diffusion-Weighted Imaging (DWI) is proposed. The proposed diagnostic approach consists of the following four steps to detect locations that are suspicious ...A new framework for early diagnosis of prostate cancer using Diffusion-Weighted Imaging (DWI) is proposed. The proposed diagnostic approach consists of the following four steps to detect locations that are suspicious for prostate cancer: 1) In the first step, we isolate the prostate from the surrounding anatomical structures based on a Maximum A Posteriori (MAP) estimate of a new log-likelihood function that accounts for the shape priori, the spatial interaction, and the current appearance of prostate tissues and its background (surrounding anatomical structures);2) In order to take into account any local deformation between the segmented prostates at different b-values that could occur during the scanning process due to local motion, a non-rigid registration algorithm is employed;3) A KNN-based classifier is used to classify the prostate into benign or malignant based on three appearance features extracted from registered images;and 4) The tumor boundaries are determined using a level set deformable model controlled by the diffusion information and the spatial interactions between the prostate voxels. Preliminary experiments on 28 patients (17 malignant and 11 benign) resulted in 100% correct classification, showing that the proposed method is a promising supplement to current technologies (biopsy-based diagnostic systems) for the early diagnosis of prostate cancer.展开更多
文摘We present a case of left ectopic ureter insertion into the left seminal vesicle which is a rare anomaly.The incidence of ectopic insertion of the ureter is more common in females and is usually associated with incontinence,leading to the diagnosis,while in males it is present with infection.Ectopic ureter is defined as abnormal insertion of the ureter,occurring in the posterior urethra in approximately 50%of cases in males.Other sites include the seminal vesicle(approximately one-third),vas deferens,bladder neck,prostate and epididymis,while the urethra and vagina are commonly affected in females.Management is usually addressed to the upper tract only;if there is incontinence it requires removal of the ureteric stump.Our case was initially diagnosed by magnetic resonance imaging and the diagnosis confirmed by computed tomography(CT)guided seminal vesiculography as transrectal guidance for seminal vesiculography was refused by the patient.CT guided seminal vesiculography is less painful and more tolerable than the transrectal route.
文摘A new framework for early diagnosis of prostate cancer using Diffusion-Weighted Imaging (DWI) is proposed. The proposed diagnostic approach consists of the following four steps to detect locations that are suspicious for prostate cancer: 1) In the first step, we isolate the prostate from the surrounding anatomical structures based on a Maximum A Posteriori (MAP) estimate of a new log-likelihood function that accounts for the shape priori, the spatial interaction, and the current appearance of prostate tissues and its background (surrounding anatomical structures);2) In order to take into account any local deformation between the segmented prostates at different b-values that could occur during the scanning process due to local motion, a non-rigid registration algorithm is employed;3) A KNN-based classifier is used to classify the prostate into benign or malignant based on three appearance features extracted from registered images;and 4) The tumor boundaries are determined using a level set deformable model controlled by the diffusion information and the spatial interactions between the prostate voxels. Preliminary experiments on 28 patients (17 malignant and 11 benign) resulted in 100% correct classification, showing that the proposed method is a promising supplement to current technologies (biopsy-based diagnostic systems) for the early diagnosis of prostate cancer.
