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Pneumoconiosis, an occupational respiratory illness triggered by inhaling mineral dust with increasing prevalence and severity worldwide. Chest radiograph plays a vital role in the screening of pneumoconiosis. The pneumoconiosis staging mainly depends on the small opacity in the lung fields, and early-stage pneumoconiosis staging has been a challenging task, necessitating quantitative diagnostics. Thoracic Computed Tomography (CT) images represent the gold-standard modality for evaluating local abnormalities and understanding structure-function relationships in an organ. The thoracic CT images have the potential to provide an essential feature for distinguishing subtle morphological patterns of micro-nodule distributions in the lungs through quantitative analyses. This study investigates whether quantitative representations based on topological data analysis can capture particulate shadows' three-dimensional (3D) distribution properties in pneumoconiosis in volumetric CT images.
Conference Presentation
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
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R. Nii, Y. Kawata, Y. Ohtsuka, T. Kishimoto, K. Ashizawa, N. Niki, "Micronodule analysis by severity of pneumoconiosis using 3D CT images," Proc. SPIE 12931, Medical Imaging 2024: Imaging Informatics for Healthcare, Research, and Applications, 1293110 (2 April 2024); https://doi.org/10.1117/12.3009095