The renaissance of deep learning has provided promising solutions to various tasks. While
conventional deep learning models are constructed for a single specific task, multi-task deep …

Prostate segmentation in transrectal ultrasound (TRUS) image is an essential prerequisite
for many prostate-related clinical procedures, which, however, is also a long-standing …

Acquiring pixel-level annotations is often limited in applications such as histology studies
that require domain expertise. Various semi-supervised learning approaches have been …

Background Previous studies have explored the potential on radiomics features of primary
breast cancer tumor to identify axillary lymph node (ALN) metastasis. However, the value of …

Introduction: Prostate cancer (PCa) is one of the deadliest and most common causes of
malignancy and death in men worldwide, with a higher prevalence and mortality in …

Automatically and accurately annotating tumor in dynamic contrast-enhanced magnetic
resonance imaging (DCE-MRI), which provides a noninvasive in vivo method to evaluate …

Prostate cancer is one of the most commonly diagnosed non-cutaneous malignant tumors
and the sixth major cause of cancer-related death generally found in men globally …

Automated segmentation of liver tumors in CT scans is pivotal for diagnosing and treating
liver cancer, offering a valuable alternative to labor-intensive manual processes and …

Automatic and accurate prostate ultrasound segmentation is a long-standing and
challenging problem due to the severe noise and ambiguous/missing prostate boundaries …

Deep learning advanced to one of the most important technologies in almost all medical
fields. Especially in areas, related to medical imaging it plays a big role. However, in …