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Proceedings Paper

Computer-assisted polyp matching between optical colonoscopy and CT colonography: a phantom study
Author(s): Holger R. Roth; Thomas E. Hampshire; Emma Helbren; Mingxing Hu; Roser Vega; Steve Halligan; David J. Hawkes
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Paper Abstract

Potentially precancerous polyps detected with CT colonography (CTC) need to be removed subsequently, using an optical colonoscope (OC). Due to large colonic deformations induced by the colonoscope, even very experienced colonoscopists find it difficult to pinpoint the exact location of the colonoscope tip in relation to polyps reported on CTC. This can cause unduly prolonged OC examinations that are stressful for the patient, colonoscopist and supporting staff. We developed a method, based on monocular 3D reconstruction from OC images, that automatically matches polyps observed in OC with polyps reported on prior CTC. A matching cost is computed, using rigid point-based registration between surface point clouds extracted from both modalities. A 3D printed and painted phantom of a 25 cm long transverse colon segment was used to validate the method on two medium sized polyps. Results indicate that the matching cost is smaller at the correct corresponding polyp between OC and CTC: the value is 3.9 times higher at the incorrect polyp, comparing the correct match between polyps to the incorrect match. Furthermore, we evaluate the matching of the reconstructed polyp from OC with other colonic endoluminal surface structures such as haustral folds and show that there is a minimum at the correct polyp from CTC. Automated matching between polyps observed at OC and prior CTC would facilitate the biopsy or removal of true-positive pathology or exclusion of false-positive CTC findings, and would reduce colonoscopy false-negative (missed) polyps. Ultimately, such a method might reduce healthcare costs, patient inconvenience and discomfort.

Paper Details

Date Published: 12 March 2014
PDF: 8 pages
Proc. SPIE 9036, Medical Imaging 2014: Image-Guided Procedures, Robotic Interventions, and Modeling, 903609 (12 March 2014); doi: 10.1117/12.2042860
Show Author Affiliations
Holger R. Roth, Univ. College London (United Kingdom)
Thomas E. Hampshire, Univ. College London (United Kingdom)
Emma Helbren, Univ. College London (United Kingdom)
Mingxing Hu, Univ. College London (United Kingdom)
Roser Vega, Univ. College Hospital (United Kingdom)
Steve Halligan, Univ. College London (United Kingdom)
David J. Hawkes, Univ. College London (United Kingdom)

Published in SPIE Proceedings Vol. 9036:
Medical Imaging 2014: Image-Guided Procedures, Robotic Interventions, and Modeling
Ziv R. Yaniv; David R. Holmes, Editor(s)

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