Purpose To investigate the accuracy and robustness of prostate segmentation using deep
learning across various training data sizes, MRI vendors, prostate zones, and testing …

Multiparametric prostate magnetic resonance imaging (mpMRI) is widely used as a triage
test for men at a risk of prostate cancer. However, the traditional role of mpMRI was confined …

Medical image segmentation enables doctors to observe lesion regions better and make
accurate diagnostic decisions. Single-branch models such as U-Net have achieved great …

The production of blood cells is affected by leukemia, a type of bone marrow cancer or blood
cancer. Deoxyribonucleic acid (DNA) is related to immature cells, particularly white cells …

Leukemia is a kind of blood cancer that influences people of all ages and is one of the
leading causes of death worldwide. Acute lymphoblastic leukemia (ALL) is the most widely …

Background: In the field of biomedical imaging, radiomics is a promising approach that aims
to provide quantitative features from images. It is highly dependent on accurate identification …

In healthcare, a growing number of physicians and support staff are striving to facilitate
personalized radiotherapy regimens for patients with prostate cancer. This is because …

Prostate cancer (PCa) represents the fourth most common cancer and the fifth leading cause
of cancer death of men worldwide. Multiparametric MRI (mp-MRI) has high sensitivity and …

Glioma is the most common primary tumor in the skull, but it has no obvious boundary with
normal brain tissue and is difficult to completely remove. Currently, manual segmentation of …

Purpose Aim of this study was to evaluate a fully automated deep learning network named
Efficient Neural Network (ENet) for segmentation of prostate gland with median lobe …