Enhanced Nuclei Segmentation in Histopathology Image Leveraging RGB Channels through Triple-Encoder and Single-Decoder Architectures
Author:
Affiliation:
1. Inje University,Digital Anti-Aging Health Care,Gimhae-si,Gyeongsangnam-do,Republic of Korea
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10315953/10315721/10316131.pdf?arnumber=10316131
Reference16 articles.
1. A review and comparison of breast tumor cell nuclei segmentation performances using deep convolutional neural networks;lagree;Scientific Reports,2021
2. Multi-channel Deep Transfer Learning for Nuclei Segmentation in Glioblastoma Cell Tissue Images
3. Skip-connection convolutional neural network for still image crowd counting
4. Deep structured residual encoder-decoder network with a novel loss function for nuclei segmentation of kidney and breast histopathology images
5. A method for normalizing histology slides for quantitative analysis
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