Paper
3 March 2017 Detection of juxta-pleural lung nodules in computed tomography images
Guilherme Aresta, António Cunha, Aurélio Campilho
Author Affiliations +
Abstract
A method for the detection of juxta-pleural lung nodules with radius ≤ 5mm in chest computed tomography images is proposed. The lung volume is segmented using region-growing and refined with morphological operations and active contours to include juxta-pleural nodules. Nodule candidates are searched slice-wise inside the lung volume segmentation. Solid nodules are detected by selecting an appropriate threshold inside a representative sliding window. Sub-solid and non-solid nodules are enhanced with a multiscale Laplacian-of-Gaussian filtering prior to their detection. Obvious non-nodule candidates, namely small blood vessels, are discarded using fixed rules. Then, a support vector machine with radial basis function is trained with the remaining candidates to further reduce the number of false positives (FPs). The final system sensitivity is 57.4% with 4 FPs/scan.The performance is similar or better than state-of-the-art methods, especially when considering the high number and small radius of the studied juxta-pleural nodules.
© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Guilherme Aresta, António Cunha, and Aurélio Campilho "Detection of juxta-pleural lung nodules in computed tomography images", Proc. SPIE 10134, Medical Imaging 2017: Computer-Aided Diagnosis, 101343N (3 March 2017); https://doi.org/10.1117/12.2252022
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Cited by 8 scholarly publications.
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KEYWORDS
Lung

Volume rendering

Computed tomography

Blood vessels

Computer aided diagnosis and therapy

Chest

Machine learning

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