Automatic Diagnosis of Pectus Excavatum from CT Images Using a Joint CNN-LSTM Model-Reference-Cited by-同舟云学术

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Automatic Diagnosis of Pectus Excavatum from CT Images Using a Joint CNN-LSTM Model

Published:2023-07-03 Issue: Volume: Page:
ISSN:
Container-title:2023 9th International Conference on Control, Decision and Information Technologies (CoDIT)
language:
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Author:

Liao Yizhi¹,Zhou Haiyu²,Xie Longhan³,Cai Siqi⁴

Affiliation:

1. School of Computing and Information Systems, University of Melbourne,Melbourne,Australia

2. Guangdong Lung Cancer Institute, Guangdong Provincial People's Hospital,Division of Thoracic Surgery,Guangzhou,China

3. Shien-Ming Wu School of Intelligent Engineering, South China University of Technology,Guangzhou,China

4. National University of Singapore,Department of Electrical and Computer Engineering,Singapore

Funder

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10284032/10284045/10284352.pdf?arnumber=10284352

Reference17 articles.

1. Brain tumor classification for MR images using transfer learning and fine-tuning

2. CNN-LSTM: Cascaded Framework For Brain Tumour Classification

3. A deep learning method for bearing fault diagnosis based on Cyclic Spectral Coherence and Convolutional Neural Networks

4. Deep Convolutional Neural Networks for breast cancer screening

5. Feasible Study on Intracranial Hemorrhage Detection and Classification using a CNN-LSTM Network

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