Single nucleus segmentation is a frequent challenge of microscopy image processing, since
it is the first step of many quantitative data analysis pipelines. The quality of tracking single …

Machine learning has become an increasingly ubiquitous technology, as big data continues
to inform and influence everyday life and decision-making. Currently, in medicine and …

Nucleus segmentation is an imperative step in the qualitative study of imaging datasets,
considered as an intricate task in histopathology image analysis. Segmenting a nucleus is …

Abnormalities in biological cell nuclei shapes are correlated with cell cycle stages, disease
states, and various external stimuli. There have been many deep learning approaches that …

Recent advances in whole‐slide imaging (WSI) technology have led to the development of a
myriad of computer vision and artificial intelligence‐based diagnostic, prognostic, and …

Deep Learning (DL) is rapidly permeating the field of Digital Pathology with algorithms
successfully applied to ease daily clinical practice and to discover novel associations …

Background and objectives The detection of tumor-infiltrating lymphocytes (TILs) could aid in
the development of objective measures of the infiltration grade and can support decision …

Examination of tissue biopsy and quantification of the various characteristics of cellular
processes are clinical benchmarks in cancer diagnosis. Nuclei and glands instance …

Medical Imaging has become a vital technique that has been embraced in the diagnosis and
treatment process of cancer. Histopathological slides, which microscopically examine the …

One of the most popular methods in the diagnosis of breast cancer is fine-needle biopsy
without aspiration. Cell nuclei are the most important elements of cancer diagnostics based …