Challenges of Deep Learning in Medical Image Analysis—Improving Explainability and Trust-Reference-Cited by-同舟云学术

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Challenges of Deep Learning in Medical Image Analysis—Improving Explainability and Trust

Published:2023-03 Issue:1 Volume:4 Page:68-75
ISSN:2637-6415
Container-title:IEEE Transactions on Technology and Society
language:
Short-container-title:IEEE Trans. Technol. Soc.

Author:

Dhar Tribikram¹^ORCID,Dey Nilanjan²^ORCID,Borra Surekha³^ORCID,Sherratt R. Simon⁴^ORCID

Affiliation:

1. Department of Electrical Engineering, Jadavpur University, Kolkata, India

2. Department of Computer Science Engineering, Techno International New Town, Kolkata, India

3. Department of Electronics and Communication Engineering, K. S. Institute of Technology, Bengaluru, India

4. Department of Biomedical Engineering, University of Reading, Reading, U.K.

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Medicine

Link

http://xplorestaging.ieee.org/ielx7/8566059/10086685/10005626.pdf?arnumber=10005626

Reference45 articles.

1. A study on 3D classical versus GAN-based augmentation for MRI brain image to predict the diagnosis of dementia with Lewy bodies and Alzheimer's disease in a European multi-center study

2. Medical Image Synthesis with Deep Convolutional Adversarial Networks

3. CT images GAN-based augmentation with AdaIN for lung nodules detection

4. Synthetic data augmentation using GAN for improved liver lesion classification

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