The semantic image segmentation task consists of classifying each pixel of an image into an
instance, where each instance corresponds to a class. This task is a part of the concept of …

Knee osteoarthritis is a major diarthrodial joint disorder with profound global socioeconomic
impact. Diagnostic imaging using magnetic resonance image can produce morphometric …

The nuclear protein Ki-67 and Tumor infiltrating lymphocytes (TILs) have been introduced as
prognostic factors in predicting both tumor progression and probable response to …

Background Pretraining labeled datasets, like ImageNet, have become a technical standard
in advanced medical image analysis. However, the emergence of self-supervised learning …

A computer-aided diagnosis system is one of the crucial decision support tools under the
medical imaging scope. It has recently emerged as a powerful way to diagnose Alzheimer's …

Temporal bone CT-scan is a prerequisite in most surgical procedures concerning the ear
such as cochlear implants. The 3D vision of inner ear structures is crucial for diagnostic and …

Accurate segmentation of brain tumors from magnetic resonance (MR) images play a pivot
role in assisting diagnoses, treatments and postoperative evaluations. However, due to its …

The Grade of meningioma has significant implications for selecting treatment regimens
ranging from observation to surgical resection with adjuvant radiation. For most patients …

Accurate segmentation of rectal tumors is the most crucial task in determining the stage of
rectal cancer and develo** suitable therapies. However, complex image backgrounds …

Methods for the automated segmentation of brain structures are a major subject of medical
research. The small structures of the deep brain have received scant attention, notably for …