The size of nuclei in histological preparations from excised breast tumors is predictive of patient outcome (large nuclei indicate poor outcome). Pathologists take into account nuclear size when performing breast cancer grading. In addition, the mean nuclear area (MNA) has been shown to have independent prognostic value. The straightforward approach to measuring nuclear size is by performing nu...

A vast array of pathologies is typified by the presence of nuclei with an abnormal morphology. Dysmorphic nuclear phenotypes feature dramatic size changes or foldings, but also entail much subtler deviations such as nuclear protrusions called blebs. Due to their unpredictable size, shape and intensity, dysmorphic nuclei are often not accurately detected in standard image analysis routines. To e...

In digital pathology, various biomarkers (e.g., KI67, HER2, CD3/CD8) are routinely analyzed by pathologists through immuno-histo-chemistry-stained slides. Identifying these on patient biopsies allows for a more informed design of their treatment regimen. The diversity and specificity types images make the availability annotated databases sparse. Consequently, robust efficient learning-based dia...

Neural stem cells derived from both embryonic and adult brain can be cultured as neurospheres; a free floating 3-D aggregate of cells. Neurospheres represent a heterogenous mix of cells including neural stem and progenitor cells. In order to investigate the self-renewal, growth and differentiation of cells within neurospheres, it is crucial that individual nuclei are accurately identified using...

Histopathology imaging provides high resolution multispectral images for study and diagnosis of various types of cancers. The automatic analysis of these images can greatly facilitate the diagnosis task for pathologists. A primary step in computational histology is accurate image segmentation to detect the number and spatial distribution of cell nuclei in the tissue, along with segmenting other...

Segmentation of intact cell nuclei from three-dimensional (3D) images of thick tissue sections is an important basic capability necessary for many biological research studies. However, segmentation is often difficult because of the tight clustering of nuclei in many specimen types. We present a 3D segmentation approach that combines the recognition capabilities of the human visual system with t...

This thesis presents contributions in the field of microscopic image analysis, in particular the automatic segmentation of fluorescent images of cell nuclei and colon crypts. The evaluation methodology of the segmentation results is detailed and a new evaluation criterion is presented. The proposed discrepancy method is based on the comparison: machine segmentation vs. ground-truth segmentation...

In this research work, to understand the types of cancer cell and attempt to analyses the biopsy slides. In this method to identify cancer parts just using simple technique of isolation of insignificant portion of biopsy slide by cancer cell level and object level segmentation and classification. Many features used in the cancer cell detection and classification of biopsy image are inspired by ...

Segmentation, condensation and bilateral symmetry of the nuclei of polymorphonuclear leukocytes seem related to their function. Segmentation of the nuclei into two or more lobes and their condensation facilitate their passage (diapedesis) through the endothelial layer of blood vessels to the extravasal space and subsequent locomotion through the interstitial compartment of different tissues. Bi...

In this paper, we propose a novel, completely automated method for the segmentation of lymphatic cell nuclei represented in microscopic specimen images. Actually, segmenting cell nuclei is the first, necessary step for developing an automated application for the early diagnostics of lymphatic system tumors. The proposed method follows a two-step approach to, firstly, find the nuclei and, then, ...