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A Comprehensive Survey on the Progress, Process, and Challenges of Lung Cancer Detection and Classification
M F Mridha1, Akibur Rahman Prodeep2, A S M Morshedul Hoque2
1Department of Computer Science and Engineering, American International University Bangladesh, Dhaka 1229, Bangladesh.
Journal of Healthcare Engineering
|December 26, 2022
Summary
This review offers a comprehensive overview of automated lung cancer detection using medical imaging. It covers datasets, preprocessing, segmentation, feature extraction, and classifiers for early diagnosis.
Area of Science:
- Oncology
- Medical Imaging Analysis
- Artificial Intelligence in Healthcare
Background:
- Lung cancer is a leading cause of cancer mortality globally, with increasing death rates.
- Early detection significantly improves recovery chances, but radiologist workload and limited numbers hinder timely diagnosis.
- Automated methods using medical imaging are crucial for rapid and accurate lung cancer prediction.
Conclusions:
- A comprehensive review of automated lung cancer detection methods is presented, covering the entire pipeline from data to classification.
- The paper highlights the importance of AI in overcoming radiologist limitations for early and accurate lung cancer diagnosis.
- Future directions and potential solutions for existing challenges in lung cancer image analysis are discussed.
