Robust nucleus/cell detection and segmentation in digital pathology and microscopy images: a comprehensive review
Digital pathology and microscopy image analysis is widely used for comprehensive studies
of cell morphology or tissue structure. Manual assessment is labor intensive and prone to …
of cell morphology or tissue structure. Manual assessment is labor intensive and prone to …
A review: The detection of cancer cells in histopathology based on machine vision
W He, T Liu, Y Han, W Ming, J Du, Y Liu, Y Yang… - Computers in Biology …, 2022 - Elsevier
Abstract Machine vision is being employed in defect detection, size measurement, pattern
recognition, image fusion, target tracking and 3D reconstruction. Traditional cancer detection …
recognition, image fusion, target tracking and 3D reconstruction. Traditional cancer detection …
Hover-net: Simultaneous segmentation and classification of nuclei in multi-tissue histology images
Nuclear segmentation and classification within Haematoxylin & Eosin stained histology
images is a fundamental prerequisite in the digital pathology work-flow. The development of …
images is a fundamental prerequisite in the digital pathology work-flow. The development of …
Star-convex polyhedra for 3D object detection and segmentation in microscopy
Accurate detection and segmentation of cell nuclei in volumetric (3D) fluorescence
microscopy datasets is an important step in many biomedical research projects. Although …
microscopy datasets is an important step in many biomedical research projects. Although …
A dataset and a technique for generalized nuclear segmentation for computational pathology
Nuclear segmentation in digital microscopic tissue images can enable extraction of high-
quality features for nuclear morphometrics and other analysis in computational pathology …
quality features for nuclear morphometrics and other analysis in computational pathology …
Segmentation of nuclei in histopathology images by deep regression of the distance map
The advent of digital pathology provides us with the challenging opportunity to automatically
analyze whole slides of diseased tissue in order to derive quantitative profiles that can be …
analyze whole slides of diseased tissue in order to derive quantitative profiles that can be …
[HTML][HTML] Cellvit: Vision transformers for precise cell segmentation and classification
Nuclei detection and segmentation in hematoxylin and eosin-stained (H&E) tissue images
are important clinical tasks and crucial for a wide range of applications. However, it is a …
are important clinical tasks and crucial for a wide range of applications. However, it is a …
An automatic learning-based framework for robust nucleus segmentation
Computer-aided image analysis of histopathology specimens could potentially provide
support for early detection and improved characterization of diseases such as brain tumor …
support for early detection and improved characterization of diseases such as brain tumor …
Cia-net: Robust nuclei instance segmentation with contour-aware information aggregation
Accurate segmenting nuclei instances is a crucial step in computer-aided image analysis to
extract rich features for cellular estimation and following diagnosis as well as treatment …
extract rich features for cellular estimation and following diagnosis as well as treatment …
Accurate segmentation of cervical cytoplasm and nuclei based on multiscale convolutional network and graph partitioning
In this paper, a multiscale convolutional network (MSCN) and graph-partitioning-based
method is proposed for accurate segmentation of cervical cytoplasm and nuclei. Specifically …
method is proposed for accurate segmentation of cervical cytoplasm and nuclei. Specifically …