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HAPNet: hierarchically aggregated pyramid network for real-time stereo matching

Brandao, P; Psychogyios, D; Mazomenos, E; Stoyanov, D; Janatka, M; (2020) HAPNet: hierarchically aggregated pyramid network for real-time stereo matching. Computer Methods in Biomechanics and Biomedical Engineering: Imaging and Visualization 10.1080/21681163.2020.1835561. (In press).

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Computer Methods in Biomechanics and Biomedical Engineering Imaging and Visualization_2020_accepted.pdf - Accepted version
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Abstract

©Recovering the 3D shape of the surgical site is crucial for multiple computer-assisted interventions. Stereo endoscopes can be used to compute 3D depth but computational stereo is a challenging, non-convex and inherently discontinuous optimisation problem. In this paper, we propose a deep learning architecture which avoids the explicit construction of a cost volume of similarity which is one of the most computationally costly blocks of stereo algorithms. This makes training our network significantly more efficient and avoids the needs for large memory allocation. Our method performs well, especially around regions comprising multiple discontinuities around surgical instrumentation or around complex small structures and instruments. The method compares well to the state-of-the-art techniques while taking a different methodological angle to computational stereo problem in surgical video.

Type: Article
Title: HAPNet: hierarchically aggregated pyramid network for real-time stereo matching
DOI: 10.1080/21681163.2020.1835561
Publisher version: https://dx.doi.org/10.1080/21681163.2020.1835561
Language: English
Additional information: Convolutional neural networks, colonoscopy, computer-aided diagnosis
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Med Phys and Biomedical Eng
URI: https://discovery.ucl.ac.uk/id/eprint/10122492
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