TY - GEN
T1 - Targeted optical biopsies for surveillance endoscopies
AU - Atasoy, Selen
AU - Mateus, Diana
AU - Meining, Alexander
AU - Yang, Guang Zhong
AU - Navab, Nassir
PY - 2011
Y1 - 2011
N2 - 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 (S1), 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.
AB - 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 (S1), 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.
UR - http://www.scopus.com/inward/record.url?scp=82255181738&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-23626-6_11
DO - 10.1007/978-3-642-23626-6_11
M3 - Conference contribution
C2 - 22003687
AN - SCOPUS:82255181738
SN - 9783642236259
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 83
EP - 90
BT - Medical Image Computing and Computer-Assisted Intervention, MICCAI 2011 - 14th International Conference, Proceedings
T2 - 14th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2011
Y2 - 18 September 2011 through 22 September 2011
ER -