Selective Attention UNet for Segmenting Liver Tumors-Reference-Cited by-同舟云学术

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Selective Attention UNet for Segmenting Liver Tumors

Published:2023-10-20 Issue: Volume: Page:
ISSN:
Container-title:2023 International Conference on Cyber-Physical Social Intelligence (ICCSI)
language:
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Author:

Patil Darshan¹,Sakarkar Gopal²,Khatri Pearl³,Khedkar Atharva¹,Gan Hong-Seng⁴,Ramlee Muhammad Hanif⁵

Affiliation:

1. G. H. Raisoni College of Engineering,Dept. of Artificial Intelligence,Nagpur,India

2. Dr. Vishwanath Karad MIT world peace University,School of Computer Science,Kothrud,Pune

3. Banasthali Vidyapith,Dept. of Computer Science,Jaipur,India

4. Xi’an Jiaotong-Liverpool University,School of AI and Advanced Computing,Suzhou,China

5. Universiti Teknologi Malaysia,Dept. of Biomedical Engineering,Johor,Malaysia

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10303765/10303774/10303778.pdf?arnumber=10303778

Reference21 articles.

1. Semi-automatic Segmentation of 3D Liver Tumors from CT Scans Using Voxel Classification and Propagational Learning

2. Random feature subspace ensemble based Extreme Learning Machine for liver tumor detection and segmentation

3. Automatic Liver and Lesion Segmentation in CT Using Cascaded Fully Convolutional Neural Networks and 3D Conditional Random Fields

4. Machine learning analysis of whole mouse brain vasculature

5. Automatic liver and tumor segmentation of CT and MRI volumes using cascaded fully convolutional neural networks;christ;arXiv preprint arXiv 1702 05464,2017

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