Combining Multistaged Filters and Modified Segmentation Network for Improving Lung Nodules Classification-Reference-Cited by-同舟云学术

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Combining Multistaged Filters and Modified Segmentation Network for Improving Lung Nodules Classification

Published:2024-09 Issue:9 Volume:28 Page:5519-5527
ISSN:2168-2194
Container-title:IEEE Journal of Biomedical and Health Informatics
language:
Short-container-title:IEEE J. Biomed. Health Inform.

Author:

Gunawan Rudy¹^ORCID,Tran Yvonne²^ORCID,Zheng Jinchuan¹^ORCID,Nguyen Hung¹^ORCID,Carrigan Ann³^ORCID,Mills Megan K.⁴^ORCID,Chai Rifai¹^ORCID

Affiliation:

1. School of Science, Computing and Engineering Technologies, Swinburne University, Melbourne, VIC, Australia

2. Macquarie University Hearing, Macquarie University, Sydney, NSW, Australia

3. Australian Institute of Health Innovation, Faculty of Medicine, Health and Human Sciences, Macquarie University, Sydney, NSW, Australia

4. School of Medicine, The University of Utah, Salt Lake City, UT, USA

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6221020/10666866/10540203.pdf?arnumber=10540203

Reference45 articles.

1. Low-dose CT of the lungs: preliminary observations.

2. Managing the Small Pulmonary Nodule Discovered by CT

3. Three-dimensional segmentation and growth-rate estimation of small pulmonary nodules in helical ct images

4. A tool for lung nodules analysis based on segmentation and morphological operation

5. Lung-RADS Version 1.0 versus Lung-RADS Version 1.1: Comparison of Categories Using Nodules from the National Lung Screening Trial

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1. A survey on comparative study of lung nodules applying machine learning and deep learning techniques;Multimedia Tools and Applications;2024-08-20

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