Slice-to-volume medical image registration: A survey

被引:116
作者
Ferrante, Enzo [1 ,2 ]
Paragios, Nikos [1 ,3 ]
机构
[1] Univ Paris Saclay, Ctr Visual Comp, Cent Supelec, INRIA, F-92295 Chatenay Malabry, France
[2] Imperial Coll London, Dept Comp, Biomed Image Anal BioMedlA Grp, South Kensington Campus,180 Queens Gate, London SW7 2AZ, England
[3] TheraPanacea, 24 Rue Faubourg St Jacques, F-75014 Paris, France
基金
欧洲研究理事会;
关键词
Bibliographical review; Slice-to-volume registration; Medical image registration; Medical image analysis; IN-UTERO FETAL; RESPIRATORY MOTION COMPENSATION; NONRIGID REGISTRATION; REAL-TIME; DEFORMABLE REGISTRATION; ENERGY MINIMIZATION; INTERVENTIONAL MRI; THERMAL ABLATION; REGISTERING; 2D; BRAIN MRI;
D O I
10.1016/j.media.2017.04.010
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
During the last decades, the research community of medical imaging has witnessed continuous advances in image registration methods, which pushed the limits of the state-of-the-art and enabled the development of novel medical procedures. A particular type of image registration problem, known as slice-to-volume registration, played a fundamental role in areas like image guided surgeries and volumetric image reconstruction. However, to date, and despite the extensive literature available on this topic, no survey has been written to discuss this challenging problem. This paper introduces the first comprehensive survey of the literature about slice-to-volume registration, presenting a categorical study of the algorithms according to an ad-hoc taxonomy and analyzing advantages and disadvantages of every category. We draw some general conclusions from this analysis and present our perspectives on the future of the field. (C) 2017 Elsevier B.V. All rights reserved.
引用
收藏
页码:101 / 123
页数:23
相关论文
共 183 条
  • [1] Andres B., 2012, LAZY FLIPPER EFFICIE, P154
  • [2] [Anonymous], 1943, Bull Calcutta Math Soc, DOI DOI 10.1038/157869B0
  • [3] Arbel T., 2001, Medical Image Computing and Computer-Assisted Intervention-MICCAI, V2208/2010, P913
  • [4] GENERALIZING THE HOUGH TRANSFORM TO DETECT ARBITRARY SHAPES
    BALLARD, DH
    [J]. PATTERN RECOGNITION, 1981, 13 (02) : 111 - 122
  • [5] Ultrasound-to-computer-tomography registration for image-guided laparoscopic liver surgery
    Bao, P
    Warmath, J
    Galloway, R
    Herline, A
    [J]. SURGICAL ENDOSCOPY AND OTHER INTERVENTIONAL TECHNIQUES, 2005, 19 (03): : 424 - 429
  • [6] Speeded-Up Robust Features (SURF)
    Bay, Herbert
    Ess, Andreas
    Tuytelaars, Tinne
    Van Gool, Luc
    [J]. COMPUTER VISION AND IMAGE UNDERSTANDING, 2008, 110 (03) : 346 - 359
  • [7] Shape matching and object recognition using shape contexts
    Belongie, S
    Malik, J
    Puzicha, J
    [J]. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2002, 24 (04) : 509 - 522
  • [8] BESAG J, 1986, J R STAT SOC B, V48, P259
  • [9] A METHOD FOR REGISTRATION OF 3-D SHAPES
    BESL, PJ
    MCKAY, ND
    [J]. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 1992, 14 (02) : 239 - 256
  • [10] Bhagalia R., 2009, IMPROVED FMRI TIME S