In this paper, we evaluated DeeplabV3+ model on T2W MRI scans using the I2CVB dataset, which is designed in an encoder-decoder style for the zonal segmentation of prostate regions. An important feature of DeeplabV3+ is the depth-wise separable convolutions, which allow more information to ...
2). This model was an application of a pre-existing framework originally proposed for prostate segmentation tasks. Inspired by the U-Net architecture [13] and the capabilities of fully convolutional neural networks, this network is tailored for processing MRI volumes with end-to-end training. V-...
As a result, MRI is increasingly being used to aid in the various phases of prostate cancer care, from diagnosis to treatment selection to treatment planning and follow-up. The addition of functional and metabolic MRI techniques, such as diffusion-weighted imaging (DWI), dynamic contrast-enhanced...
Magnetic resonance imaging (MRI) provides detailed anatomical images of the prostate and its zones. It has a crucial role for many diagnostic applications. Automatic segmentation such as that of the prostate and prostate zones from MR images facilitates many diagnostic and therapeutic applications. Howe...
Maeda Y, Sasakawa A, Hirase C, Yamaguchi T, Morita Y, Miyatake J, Urase F, Nomura S, Matsumura I.doi:10.4172/2168-9857.1000e108Yasuhiro MaedaAtsushi SasakawaChikara HiraseTerufumi YamaguchiYasuyoshi MoritaJun-Ichi MiyatakeFumiaki Urase
corresponding histpathology-MRI slices and achieved a Dice coefficient of 0.97卤0.01 for the prostate, a Hausdorff distance of 1.99卤0.70 mm for the prostate boundary, a urethra deviation of 3.09卤1.45 mm, and a landmark deviation of 2.80卤0.59 mm between registered histopathology images and MRI...
Needle Biopsy of the Prostate (Transrectal) Penile Squamous Cell Carcinoma in Situ (Formerly Bowen Disease) Staghorn Stone Testicular Cancer Testicular Self-Examination Urinary Sphincter Varicocele Vesicovaginal Fistula Liver and Gallbladder Disorders (6) Cirrhosis Dupuytren Contracture of the Little Finger ...
The method enhances the resolution of low-resolution (LR) prostate cancer MRI images by combining multiple MRI slices with slight spatial shifts, utilizing shared weights for feature extraction for each MRI image. Unlike super-resolution techniques in literature, the network uses perceptual loss, ...
Purpose:MRI has shown promise in identifying prostate tumors with high sensitivity and specificity for the detection of prostate cancer. Accurate segmentation of the prostate plays a key role various tasks: to accurately localize prostate boundaries for biopsy needle placement and radiotherapy, to ...
MRI provides detailed images of the human body and is essential for diagnosing various medical conditions, from neurological disorders to musculoskeletal injuries. For in-depth interpretation of MRI images, the organs, muscles and bones in the images are outlined or marked, which is known as segment...