Enhanced Pulmonary Nodule Detection and Classification Using Artificial Intelligence on LIDC-IDRI Data
Abstract
Lung cancer remains the leading cause of cancer-related mortality worldwide. Early detection of pulmonary nodules is crucial for timely diagnosis and effective treatment. Conventional computer-aided detection systems have shown limitations, including high false-positive rates and low sensitivity. Recent advances in deep learning, particularly convolutional neural networks (CNNs), have shown great potential in improving the accuracy and reliability of nodule detection and classification. This study aimed to develop and evaluate an automatic method for lung nodule detection and classification using a CNN-based architecture applied to computed tomography images from the publicly available LIDC-IDRI database.
Fields of Study & Subjects
Lung Cancer Diagnosis and Treatment
COVID-19 diagnosis using AI
Radiomics and Machine Learning in Medical Imaging
Publication details
- Journal / source
- Exploratory Research and Hypothesis in Medicine
- Publisher
- Xia & He Publishing
- Volume
- 11
- Issue
- 1
- Pages
- e00032–e00032
- Publication date
- 15 January 2026
- Language
- EN