The analysis of the microvasculature and the assessment of angiogenesis have significant
prognostic value in various diseases, including cancer. The search for invasion into the …

Based on deep learning, pancreatic cancer pathology image segmentation technology
effectively assists pathologists in achieving improved treatment outcomes. However …

Multi-class segmentation of unlabelled living cells in time-lapse light microscopy images is
challenging due to the temporal behaviour and changes in cell life cycles and the complexity …

Purpose This study aims to introduce an innovative multi-step pipeline for automatic tumor-
stroma ratio (TSR) quantification as a potential prognostic marker for pancreatic cancer …

Pancreatic cancer is one of the most aggressive and lethal malignancies in the world.
Automatic and accurate segmentation of lesion regions from histopathological images is …

Designing deep learning algorithms for gland segmentation is crucial for automatic cancer
diagnosis and prognosis. However, the expensive annotation cost hinders the development …

Purpose This study aims to introduce an innovative multi-step pipeline for automatic
tumorstroma ratio (TSR) quantification as a potential prognostic marker for pancreatic …