In this paper, we propose a statistical approach for mitosis detection in breast cancer
histological images. The proposed algorithm models the pixel intensities in mitotic and non-mitotic …

… In this paper, we propose a new epidermis segmentation technique … image patches at 512
$$\times$$ × 512 pixels, extracted and augmented from 36 digitized histopathological images …

… histopathological image analyses, the segmentation of cell … The accuracy of the automated
segmentation technique … technique for segmentation of nuclei from histopathological images. …

… for overlapping/clustered nuclei segmentation in histopathology images. Our work stands …
fine-tuned explicitly for segmenting multi-organ cancer cells in histopathological images. By …

… a decoder for the segmentation of epithelium and stroma components in histopathology images.
… , the proposed decoder could aid in improving tissue analysis in histopathology images. …

… ) a new subset of histopathology images has been created in this experiment. In this paper,
we focus on colon histopathology image classification, segmentation and clustering. However…

… 3.1 Segmentation Cytologic and histologic images prevent the generalization of segmentation
algorithms because of the inherent variability of the nuclei structures present in them. Due …

… segmentation problem in histopathological images can be considered in two different types
of scope. The first type is to locate biological objects such as cells and glands on an image […

… nuclei segmentation framework for histopathology images using … (2) weakly supervised nuclei
segmentation. The goal of the … -throughput histopathological image analysis via robust cell …

… nuclei segmentation in skin histopathological images. Qi et al. [18] proposed to detect cell
seeds in breast histopathological images by a single pass voting algorithm, and delineate cell …