… glands segmentation strategy for histological images … histological images should be acquired
at 5x or greater magnification: using a lower resolution, the cellular structures segmentation …

… overlapped nuclei in histopathology images, we used … segmentation problem. This paper
aims to develop CAD for overlapped/clustered nuclei segmentation from histopathology images…

… datasets of H&E stained histopathology images for nuclei segmentation and compare the
results … Improved automatic detection and segmentation of cell nuclei in histopathology images. …

… histological images during diagnosis. In this paper, a two-stage approach is proposed for
computing oral histology images, … in oral histological images from proposed segmented output. …

… refers to the process of identifying groups of pixels that represent cell nuclei. … cells and color
variation in histopathological images. It is one of the core operations in histopathology image …

… gland segmentation system. Forty-three hematoxylin and eosin-stained images were …
Our automated gland segmentation system was trained using these manual annotations. It …

… and quantify cancer grading from histopathological images. The proposed system is a
multi-step approach including image acquisition, pre-processing, segmentation, feature extraction, …

… detection and segmentation in whole-slide histopathology images [… For a particular type of
cancer, histopathological images … Also, the isolated tumour cells and fine details in boundaries …

… Nayak [41] explores sparse feature learning utilizing the restricted Boltzmann machine (RBM)
to describe histopathology features in clear cell kidney carcinoma (KIRC) and GBM. These …

… This result demonstrates that our method has a high generalization ability since these
images vary from tissue types to cell types. The values of AJI and F1 score of other methods in …