Fast and accurate vision‐based stereo reconstruction and motion estimation for image‐guided liver surgery. Issue 5 (19th October 2018)

• Record Type: Journal Article
• Authors: Speers, Andrew D.; Ma, Burton; Jarnagin, William R.; Himidan, Sharifa; Simpson, Amber L.; Wildes, Richard P.
• Is Part Of: Healthcare technology letters. Volume 5:Issue 5(2018)
• Page Start: 208
• Page End: 214
• Publication Date: 2018-10-19
• Subjects: phantoms -- image matching -- stereo image processing -- image reconstruction -- computerised tomography -- tumours -- motion estimation -- liver -- image registration -- medical image processing -- surgery -- cancer -- image texture -- time series; accurate vision‐based stereo reconstruction -- motion estimation -- image‐guided liver surgery -- ablation -- adjacent complex vasculature -- end‐to‐end solution -- coarse‐to‐fine stereo approach -- liver imaging -- three‐dimensional boundary recovery -- robust 3D motion estimator -- adaptive CTF matching approach -- liver phantom -- precise quantitative evaluation -- liver resection -- fast vision‐based stereo reconstruction -- oncologic outcome -- low texture regions -- adaptive windows -- time series -- volumetric computed tomography scan -- tumours; Biomedical engineering -- Periodicals; Medical technology -- Periodicals; 610.28
• DOI: 10.1049/htl.2018.5071
• Languages: English
• ISSNs: 2053-3713

Abstract

Abstract : Image‐guided liver surgery aims to enhance the precision of resection and ablation by providing fast localisation of tumours and adjacent complex vasculature to improve oncologic outcome. This Letter presents a novel end‐to‐end solution for fast stereo reconstruction and motion estimation that demonstrates high accuracy with phantom and clinical data. The authors' computationally efficient coarse‐to‐fine (CTF) stereo approach facilitates liver imaging by accounting for low texture regions, enabling precise three‐dimensional (3D) boundary recovery through the use of adaptive windows and utilising a robust 3D motion estimator to reject spurious data. To the best of their knowledge, theirs is the only adaptive CTF matching approach to reconstruction and motion estimation that registers time series of reconstructions to a single key frame for registration to a volumetric computed tomography scan. The system is evaluated empirically in controlled laboratory experiments with a liver phantom and motorised stages for precise quantitative evaluation. Additional evaluation is provided through testing with patient data during liver resection.