UNet Deep Learning Architecture for Segmentation of Vascular and Non-Vascular Images: A Microscopic Look at UNet Components Buffered With Pruning, Explainable Artificial Intelligence, and Bias-Reference-Cited by-同舟云学术

UNet Deep Learning Architecture for Segmentation of Vascular and Non-Vascular Images: A Microscopic Look at UNet Components Buffered With Pruning, Explainable Artificial Intelligence, and Bias

Published:2023 Issue: Volume:11 Page:595-645
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Suri Jasjit S.¹^ORCID,Bhagawati Mrinalini²,Agarwal Sushant³^ORCID,Paul Sudip²^ORCID,Pandey Amit⁴,Gupta Suneet K.⁴^ORCID,Saba Luca⁵^ORCID,Paraskevas Kosmas I.⁶^ORCID,Khanna Narendra N.⁷,Laird John R.⁸^ORCID,Johri Amer M.⁹^ORCID,Kalra Manudeep K.¹⁰,Fouda Mostafa M.¹¹^ORCID,Fatemi Mostafa¹²^ORCID,Naidu Subbaram¹³^ORCID

Affiliation:

1. Stroke Diagnostic and Monitoring Division, AtheroPoint, Roseville, CA, USA

2. Department of Biomedical Engineering, North-Eastern Hill University, Shillong, India

3. TechNet Cyber Solutions Pvt. Ltd., Andhra Pradesh, India

4. Department of Computer Science, Bennett University, Greater Noida, India

5. Department of Radiology, University of Cagliari, Cagliari, Italy

6. Department of Vascular Surgery, Central Clinic of Athens, Athens, Greece

7. Department of Cardiology, Indraprastha Apollo Hospitals, New Delhi, India

8. Cardiology Department, St. Helena Hospital, St. Helena, CA, USA

9. Department of Medicine, Division of Cardiology, Queen’s University, Kingston, Canada

10. Department of Radiology, Massachusetts General Hospital, Boston, MA, USA

11. Department of Electrical and Computer Engineering, Idaho State University, Pocatello, ID, USA

12. Department of Physiology and Biomedical Engineering, Mayo Clinic College of Medicine and Science, Rochester, MN, USA

13. Electrical Engineering Department, University of Minnesota, Duluth, MN, USA

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/09999432.pdf?arnumber=9999432

Reference267 articles.

1. CoLe-CNN+: Context learning - Convolutional neural network for COVID-19-Ground-Glass-Opacities detection and segmentation

2. Eight pruning deep learning models for low storage and high-speed COVID-19 computed tomography lung segmentation and heatmap-based lesion localization: A multicenter study using COVLIAS 2.0

3. Evaluating the Association Between Comorbidities and COVID-19 Severity Scoring on Chest CT Examinations Between the Two Waves of COVID-19: An Imaging Study Using Artificial Intelligence

4. GP-Unet: Lesion Detection from Weak Labels with a 3D Regression Network

5. MSDS-UNet: A multi-scale deeply supervised 3D U-Net for automatic segmentation of lung tumor in CT

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