Neural networks have achieved outstanding performance in retinal vessel segmentation.
However, since its continuous upsampling and convolution operation in the decoding stage …

Accurate nuclei segmentation is a critical step for physicians to achieve essential information
about a patient's disease through digital pathology images, enabling an effective diagnosis …

Harvesting apples is one of the most apple-challenging operations; its process is labor-
intensive, and for various reasons, automation has yet to advance as swiftly as it might …

In spite of achieving human-level efficacy in gland and nuclei segmentation, modern deep
learning-driven techniques still face challenges related to the loss of regional context …

Cell nuclei segmentation, the task of identifying the precise boundary of the nucleus in each
cell in a histopathology image, is a rudimentary task prior to single-cell analysis. While …

This paper presents a technique that can potentially help to determine the receptivity stage
of the endometrium from histology images by automatically measuring the stromal nuclear …

Manually annotating nuclei from the gigapixel Hematoxylin and Eosin (H&E)-stained Whole
Slide Images (WSIs) is a laborious and costly task, meaning automated algorithms for cell …

Existing nuclei segmentation methods face challenges with hematoxylin and eosin (H&E)
whole slide imaging (WSI) due to the variations in staining methods and nuclei shapes and …

Precise cell nucleus segmentation is very critical in many biologically related analy-ses and
disease diagnoses. Two of the major challenges in this task are the precise delineation of …

This paper presents a method for automatic identification of endometrial glands in color, HE
stained histology images. The three processing phases that make up the proposed method …