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Presentation + Paper
15 February 2021 Towards deep learning detection of lung nodules using micro-CT
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We are developing imaging methods for the preclinical arm of a co-clinical trial investigating synergy between immunotherapy and radiotherapy. We perform in vivo micro-CT of mouse lungs to detect lung metastasis after treatment. This work explores deep learning (DL) as a fast and accurate approach to lung nodule segmentation. We examine the performance of DL lung tumor detection using realistically simulated nodules inserted into temporally-resolved real micro-CT datasets. Our simulations suggest that DL is a promising approach for fast, accurate segmentation of lung nodules in mice.
Conference Presentation
© (2021) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
M. D. Holbrook, D. P. Clark, R. Patel, Y. Qi, Y. M. Mowery, and C. T. Badea "Towards deep learning detection of lung nodules using micro-CT", Proc. SPIE 11600, Medical Imaging 2021: Biomedical Applications in Molecular, Structural, and Functional Imaging, 116000I (15 February 2021);

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