… ] pathology specimens including TMAs. Segmenting individual cells in digitized histopathology
… color and texture features to segment prostate cancer specimens was proposed in [12]. A …

… histopathological image analysis. In the following sections, we introduce the details of robust
cell segmentation … specimens using parallel seed detection and repulsive level set. TBME, …

… Computer-aided diagnosis of histopathological images usually requires … a robust and
scalable solution to enable such analysis in a real-time fashion. Specifically, a robust segmentation …

… Histopathology images are generated from specimens using a microscope camera and … ,
specimen preparation, and scanning situations. But consistent color features of histopathology …

… images of breast and prostate biopsy specimens. Xu et al. [29] incorporated a markov … deep
learning and AC model for segmenting breast cancer histopathology images, in which deep …

… In this paper, we have presented a robust, fast and accurate segmentation algorithm for
digitized tissue microarray images. A novel aspect of this algorithm is that instead of building …

… an automated cancerous cell segmentation method in both … do not apply to the lung tissue
specimens we used. In comparison, … In this paper, a robust tumour segmentation technique is …

… Precise tissue segmentation is particularly significant for a … of a specimen is very porous,
such as skin specimens. In this … segmentation in histopatological images of skin specimens …

… , a substantial amount of tissue specimens is currently scanned at a … tool for tissue segmentation
that is accurate, robust, and … and high quality and quantity tissue specimen imaging data. …

… We have applied CST for the automatic segmentation of epithelium in IHC-stained cervical
… can make a robust segmentation very challenging. Automatic segmentation is a prerequisite …