Nuclei Segmentation in Colon Histology Images by Using the Deep CNNs: A U-Net Based Multi-class Segmentation Analysis-Reference-Cited by-同舟云学术

Nuclei Segmentation in Colon Histology Images by Using the Deep CNNs: A U-Net Based Multi-class Segmentation Analysis

Published:2022-10-31 Issue: Volume: Page:
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Container-title:2022 Medical Technologies Congress (TIPTEKNO)
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Author:

Yildiz Serdar¹,Memis Abbas¹,Varl Songul¹

Affiliation:

1. Yildiz Technical University,Department of Computer Engineering,İstanbul,Turkey

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9960140/9959864/09960188.pdf?arnumber=9960188

Reference16 articles.

1. NucleiSegNet: Robust deep learning architecture for the nuclei segmentation of liver cancer histopathology images

2. MDC-net: A new convolutional neural network for nucleus segmentation in histopathology images with distance maps and contour information

3. DenseRes-Unet: Segmentation of overlapped/clustered nuclei from multi organ histopathology images

4. Deep Learning Model for Cell Nuclei Segmentation and Lymphocyte Identification in Whole Slide Histology Images

5. U-net: Convolutional net-works for biomedical image segmentation;ronneberger;International Conference on Medical Image Computing and Computer-Assisted Intervention,2015

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