Feature fusion, the combination of features from different layers or branches, is an
omnipresent part of modern network architectures. It is often implemented via simple …

Artificial intelligence (AI) in medicine has gained a lot of momentum in the last decades and
has been applied to various fields of medicine. Advances in computer science, medical …

A multitude of studies have explored the role of artificial intelligence (AI) in providing
diagnostic support to radiologists, pathologists, and urologists in prostate cancer detection …

Automatic assessing the location and extent of liver and liver tumor is critical for radiologists,
diagnosis and the clinical process. In recent years, a large number of variants of U-Net …

Automated prostate segmentation in MRI is highly demanded for computer-assisted
diagnosis. Recently, a variety of deep learning methods have achieved remarkable progress …

In medical image analysis, it is typical to collect multiple annotations, each from a different
clinical expert or rater, in the expectation that possible diagnostic errors could be mitigated …

Various deep learning methods have been proposed to segment breast lesions from
ultrasound images. However, similar intensity distributions, variable tumor morphologies …

Automatic gastric tumor segmentation and lymph node (LN) classification not only can assist
radiologists in reading images, but also provide image-guided clinical diagnosis and …

Multimodal positron emission tomography-computed tomography (PET-CT) is used routinely
in the assessment of cancer. PET-CT combines the high sensitivity for tumor detection of …

Automatic vessel segmentation in the fundus images plays an important role in the
screening, diagnosis, treatment, and evaluation of various cardiovascular and …