[HTML][HTML] Improving generalization capability of deep learning-based nuclei instance segmentation by non-deterministic train time and deterministic test time stain …
With the advent of digital pathology and microscopic systems that can scan and save whole
slide histological images automatically, there is a growing trend to use computerized …
slide histological images automatically, there is a growing trend to use computerized …
NuInsSeg: A fully annotated dataset for nuclei instance segmentation in H&E-stained histological images
A Mahbod, C Polak, K Feldmann, R Khan, K Gelles… - Scientific Data, 2024 - nature.com
In computational pathology, automatic nuclei instance segmentation plays an essential role
in whole slide image analysis. While many computerized approaches have been proposed …
in whole slide image analysis. While many computerized approaches have been proposed …
Investigating the impact of the bit depth of fluorescence-stained images on the performance of deep learning-based nuclei instance segmentation
Nuclei instance segmentation can be considered as a key point in the computer-mediated
analysis of histological fluorescence-stained (FS) images. Many computer-assisted …
analysis of histological fluorescence-stained (FS) images. Many computer-assisted …
Nuclei probability and centroid map network for nuclei instance segmentation in histology images
Nuclei instance segmentation is an integral step in digital pathology workflow as it is a
prerequisite for most downstream tasks such as patient survival analysis, precision …
prerequisite for most downstream tasks such as patient survival analysis, precision …
Gsn-hvnet: A lightweight, multi-task deep learning framework for nuclei segmentation and classification
Nuclei segmentation and classification are two basic and essential tasks in computer-aided
diagnosis of digital pathology images, and those deep-learning-based methods have …
diagnosis of digital pathology images, and those deep-learning-based methods have …
Instance-aware self-supervised learning for nuclei segmentation
Due to the wide existence and large morphological variances of nuclei, accurate nuclei
instance segmentation is still one of the most challenging tasks in computational pathology …
instance segmentation is still one of the most challenging tasks in computational pathology …
Which pixel to annotate: a label-efficient nuclei segmentation framework
Recently deep neural networks, which require a large amount of annotated samples, have
been widely applied in nuclei instance segmentation of H&E stained pathology images …
been widely applied in nuclei instance segmentation of H&E stained pathology images …
Nuclei instance segmentation and classification in histopathology images with stardist
Instance segmentation and classification of nuclei is an impor-tant task in computational
pathology. We show that StarDist, a deep learning nuclei segmentation method originally …
pathology. We show that StarDist, a deep learning nuclei segmentation method originally …
A fast and accurate algorithm for nuclei instance segmentation in microscopy images
Z Cheng, A Qu - IEEE Access, 2020 - ieeexplore.ieee.org
Nuclei instance segmentation within microscopy images is a fundamental task in the
pathology work-flow, based on that the meaningful nuclear features can be extracted and …
pathology work-flow, based on that the meaningful nuclear features can be extracted and …
A dual decoder u-net-based model for nuclei instance segmentation in hematoxylin and eosin-stained histological images
Even in the era of precision medicine, with various molecular tests based on omics
technologies available to improve the diagnosis process, microscopic analysis of images …
technologies available to improve the diagnosis process, microscopic analysis of images …