TransONet: Automatic Segmentation of Vasculature in Computed Tomographic Angiograms Using Deep Learning-Reference-Cited by-同舟云学术

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TransONet: Automatic Segmentation of Vasculature in Computed Tomographic Angiograms Using Deep Learning

Published:2023-12-13 Issue: Volume: Page:1312-1317
ISSN:
Container-title:2023 International Conference on Computational Science and Computational Intelligence (CSCI)
language:
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Author:

Rajeoni Alireza Bagheri¹,Pederson Breanna²,Firooz Ali¹,Abdollahi Hamed¹,Smith Andrew K.¹,Clair Daniel G.³,Lessner Susan M.⁴,Valafar Homayoun¹

Affiliation:

1. University of South Carolina,Computer Science & Engineering,Columbia,SC,USA

2. University of South Carolina, School of Medicine,Biomedical Engineering,Columbia,SC,USA

3. Vanderbilt University,Surgery,Nashville,TN,USA

4. University of South Carolina, School of Medicine,Cell Biology & Anatomy,Columbia,SC,USA

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10590067/10590000/10590344.pdf?arnumber=10590344

Reference40 articles.

1. Application of machine learning for patient response prediction to cardiac resynchronization therapy

2. Application of Machine Learning to Sleep Stage Classification

3. Lower limb arterial calcification (LLAC) scores in patients with symptomatic peripheral arterial disease are associated with increased cardiac mortality and morbidity

4. Static hand gesture recognition for American sign language using neuromorphic hardware

5. Facial Expression Recognition at the Edge: CPU vs GPU vs VPU vs TPU

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