Review of Histopathological Image Segmentation via current Deep Learning Approaches

The morphological structure such as nuclei, glands, tumors, etc. of histopathological images has been regularly analyzed by the pathologists in order to determine the extent of malignancy present. For the qualitative diagnosis, accurate detection along with segmentation of the aforesaid objects of interest is a vital requirement. As the manual annotations are operator dependent due to which they can be error-prone as well as time-consuming. Thus, a strong need for automated detection along with segmentation arises for which timely new techniques have been proposed. In this paper, the various techniques proposed for the segmenting aforesaid object of interest using deep learning proposed in the year 2017-18 are discussed

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