Fast and accurate vision-based stereo reconstruction and motion estimation for image-guided liver surgery

Healthcare Technology Letters

article

Andrew D. Speers¹  Burton Ma¹  William R. Jarnagin²  Sharifa Himidan³  Amber L. Simpson²  Richard P. Wildes¹ 

[1] Department of Electrical Engineering and Computer Science, York University;Department of Surgery, Memorial Sloan Kettering Cancer Center;Department of Surgery, The Hospital for Sick Children;Department of Surgery, University of Toronto

关键词: 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;   

DOI  :  10.1049/htl.2018.5071

学科分类：肠胃与肝脏病学

来源: Wiley

【 摘 要 】

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.

【 授权许可】

CC BY|CC BY-ND|CC BY-NC|CC BY-NC-ND