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Targeted optical biopsies for surveillance endoscopies.

Selen Atasoy 1 Diana Mateus 1 Alexander Meining 2 Guang-Zhong Yang 3 Nassir Navab 1
1 CAMPAR - Computer Aided Medical Procedures & Augmented Reality
2 TUM - Technische Universität München [München]
3 LIAMA - Brain imaging
Abstract : Recent introduction of probe-based confocal laser endomicroscopy (pCLE) allowed for the acquisition of in-vivo optical biopsies during the endoscopic examination without removing any tissue sample. The non-invasive nature of the optical biopsies makes the re-targeting of previous biopsy sites in surveillance examinations difficult due to the absence of scars or surface landmarks. In this work, we introduce a new method for recognition of optical biopsy scenes of the diagnosis endoscopy during serial surveillance examinations. To this end, together with our clinical partners, we propose a new workflow involving two-run surveillance endoscopies to reduce the ill-posedness of the task. In the first run, the endoscope is guided from the mouth to the z-line (junction from the oesophagus to the stomach). Our method relies on clustering the frames of the diagnosis and the first run surveillance (S1) endoscopy into several scenes and establishing cluster correspondences accross these videos. During the second run surveillance (S2), the scene recognition is performed in real-time and in-vivo based on the cluster correspondences. Detailed experimental results demonstrate the feasibility of the proposed approach with 89.75% recall and 80.91% precision on 3 patient datasets.
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Conference papers
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https://hal.inria.fr/hal-01693180
Contributor : Diana Mateus <>
Submitted on : Thursday, January 25, 2018 - 8:16:27 PM
Last modification on : Tuesday, March 17, 2020 - 3:14:53 AM

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  • HAL Id : hal-01693180, version 1
  • PUBMED : 22003687

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CNRS | INRA | INRIA | CIRAD | LIAMA | INRAE

Citation

Selen Atasoy, Diana Mateus, Alexander Meining, Guang-Zhong Yang, Nassir Navab. Targeted optical biopsies for surveillance endoscopies.. International Conference on Medical Image Computing and Computer Aided Interventions (MICCAI), Oct 2012, Nice, France. pp.83-90. ⟨hal-01693180⟩

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