Prostate cancer (PCa) is currently diagnosed by microscopic evaluation of biopsy samples.
Since tissue assessment heavily relies on the pathologists level of expertise and …

Nuclear structure alterations in cancer involve global genetic (mutations, amplifications,
copy number variations, translocations, etc.) and epigenetic (DNA methylation and histone …

A novel gland segmentation and classification scheme applied to an H&E histology image of
the prostate tissue is proposed. For gland segmentation, we associate appropriate nuclei …

Tissue image grading is one of the most important steps in prostate cancer diagnosis, where
the pathologist relies on the gland structure to assign a Gleason grade to the tissue image …

Background: Tumor grading, PSA concentration, and stage determine a risk of prostate
cancer patients with accuracy of about 70%. An approach based on the fractal geometrical …

Diagnosis of prostate cancer currently involves visual examination of samples for the
assignment of Gleason grades using a microscope, a time-consuming and subjective …

Prostate cancer automatic grading has attracted a lot of attention during the last years [1].
Many research efforts have been fixated on the development of computerized recognition …

Prostate cancer detection and staging is an important step towards patient treatment
selection. Advancements in digital pathology allow the application of new quantitative image …

Clinically, prostate adenocarcinoma is diagnosed by recognizing certain morphology on
histology. While the Gleason grading system has been shown to be the strongest prognostic …

Prostate Cancer is one of the most common types of cancer found in men aged over 40
years. Detection and staging is the most critical step for pathologists. This research supports …