Rescon-Net: Transfer Learning Based Nested Model for Cerebrovascular Segmentation with Aneurysm-Reference-Cited by-同舟云学术

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Rescon-Net: Transfer Learning Based Nested Model for Cerebrovascular Segmentation with Aneurysm

Published:2023-04-18 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI)
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Author:

Zhang Chaoran¹,Zhao Ming²,Xie Yixuan¹,Ma Ming³,Guo Kaiwen¹,Ding Rui¹,Jiang Hongzhen²,Xi Wei⁴,Xia Likun¹

Affiliation:

1. Capital Normal University,Laboratory of Neural Computing and Intelligent Perception (NCIP),Beijing,China,100048

2. Chinese PLA General Hospital,First Medical Center,Department of Neurosurgery,Beijing,China,100853

3. Winona State University,Department of Computer Science,Winona,MN,USA,55987

4. Chinese PLA General Hospital,Fourth Medical Center,Department of Radiology,Beijing,China,100048

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10230311/10230322/10230545.pdf?arnumber=10230545

Reference16 articles.

1. Semi-Supervised Cerebrovascular Segmentation by Hierarchical Convolutional Neural Network

2. JointVesselNet: Joint Volume-Projection Convolutional Embedding Networks for 3D Cerebrovascular Segmentation

3. Unsupervised Cerebrovascular Segmentation of TOF-MRA Images Based on Deep Neural Network and Hidden Markov Random Field Model

4. A U-Net Deep Learning Framework for High Performance Vessel Segmentation in Patients With Cerebrovascular Disease

5. SA-Net: Shuffle Attention for Deep Convolutional Neural Networks

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