Implementation of Different U-Net Architectures for Segmentation of Lung Cancer CT Images
Author:
Affiliation:
1. NIT Silchar,Department of Electronics and Communication Engineering,Assam,India
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10169127/10169124/10169245.pdf?arnumber=10169245
Reference25 articles.
1. Double U-Nets for Image Segmentation by Integrating the Region and Boundary Information
2. Cloud-YLung for Non-Small Cell Lung Cancer Histology Classification from 3D Computed Tomography Whole-Lung Scans
3. The iq-oth/nccd lung cancer dataset;kareem;Kaggle,2020
4. GA-UNet: UNet-based framework for segmentation of 2D and 3D medical images applicable on heterogeneous datasets
5. Lung Cancer Detection and Classification Based on Alexnet CNN
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1. TelLungNet - Enabling Telemedicine Utilizing an Improved U-Net Lung Image Segmentation;2024 IEEE Conference on Artificial Intelligence (CAI);2024-06-25
2. A Comparison of Gastrointestinal Image Segmentation by U-Net Based on Ensemble of U-Net Models and Single Model;2023 4th International Conference on Computer, Big Data and Artificial Intelligence (ICCBD+AI);2023-12-15
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