Fast High-Resolution Disparity Estimation for Laparoscopic Surgery

Publikation: Beitrag in Buch/Konferenzbericht/Sammelband/GutachtenBeitrag in KonferenzbandBeigetragenBegutachtung

Abstract

An intraoperative Image Guidance System (IGS), facilitating the localisation of pathological tissue or vasculature, could greatly support medical decisions during minimally invasive interventions. In our IGS for laparoscopic surgery, the 3D reconstruction of abdominal organs requires fast and accurate depth information from stereo images. To this end, we employ a state-of-the-art algorithm for dense disparity estimation. To cope with low processing performance, previous solutions used only downscaled images, and hence produced disparities of low quality. In this work, we present methods and implementations which improve and accelerate disparity estimation such that it runs with FullHD resolution images at full camera framerate.

Details

OriginalspracheEnglisch
TitelBioCAS 2022 - IEEE Biomedical Circuits and Systems Conference: Intelligent Biomedical Systems for a Better Future, Proceedings
Herausgeber (Verlag)IEEE Xplore
Seiten573-577
Seitenumfang5
ISBN (elektronisch)9781665469173
ISBN (Print)978-1-6654-6918-0
PublikationsstatusVeröffentlicht - 15 Okt. 2022
Peer-Review-StatusJa

Konferenz

Titel2022 IEEE Biomedical Circuits and Systems Conference
UntertitelIntelligent Biomedical Systems for a Better Future
KurztitelBioCAS 2022
Dauer13 - 15 Oktober 2022
OrtCYFF International Convention Center & online
StadtTaipei
LandTaiwan

Externe IDs

Mendeley 55861b01-23cb-3ec3-b412-b905bc02e7d8
Scopus 85142932768
ORCID /0000-0001-7436-0103/work/142240361
ORCID /0009-0007-1588-117X/work/160952921

Schlagworte

Schlagwörter

  • Pathology, Minimally invasive surgery, Three-dimensional displays, Image resolution, Circuits and systems, Estimation, Biological systems, Image guided surgery, neural network, machine vision, multithreading, parallelisation, stereo disparity