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Patient-specific 3d cellular automata nodule growth synthesis in lung cancer without the need of external data

Manzanera OEM, Ellis S, Baltatzis V, Nair A, Le Folgoc L, Desai S, Glocker B, Schnabel JA (2021)

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Publication Type: Conference contribution

Publication year: 2021

Journal

Publisher: IEEE Computer Society

Book Volume: 2021-April

Pages Range: 925-928

Conference Proceedings Title: Proceedings - International Symposium on Biomedical Imaging

Event location: Nice, FRA

ISBN: 9781665412469

DOI: 10.1109/ISBI48211.2021.9433893

Abstract

We propose a novel patient-specific generative approach to simulate the emergence and growth of lung nodules using 3D cellular automata (CA) in computer tomography (CT). Our proposed method can be applied to individual images thus eliminating the need of external images that can contaminate and influence the generative process, a valuable characteristic in the medical domain. Firstly, we employ inpainting to generate pseudo-healthy representations of lung CT scans prior the visible appearance of each lung nodule. Then, for each nodule, we train a 3D CA to simulate nodule growth and progression using the image of that same nodule as a target. After each CA is trained, we generate early versions of each nodule from a single voxel until the growing nodule closely matches the appearance of the original nodule. These synthesized nodules are inserted where the original nodule was located in the pseudo-healthy inpainted versions of the CTs, which provide realistic context to the generated nodule. We utilize the simulated images for data augmentation yielding false positive reduction in a nodule detector. We found statistically significant improvements (p lt 0.001) in the detection of lung nodules.

Involved external institutions

How to cite

APA:

Manzanera, O.E.M., Ellis, S., Baltatzis, V., Nair, A., Le Folgoc, L., Desai, S.,... Schnabel, J.A. (2021). Patient-specific 3d cellular automata nodule growth synthesis in lung cancer without the need of external data. In Proceedings - International Symposium on Biomedical Imaging (pp. 925-928). Nice, FRA: IEEE Computer Society.

MLA:

Manzanera, Octavio E. Martinez, et al. "Patient-specific 3d cellular automata nodule growth synthesis in lung cancer without the need of external data." Proceedings of the 18th IEEE International Symposium on Biomedical Imaging, ISBI 2021, Nice, FRA IEEE Computer Society, 2021. 925-928.

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