Literature DB >> 9874298

Surface-based registration of CT images to physical space for image-guided surgery of the spine: a sensitivity study.

J L Herring1, B M Dawant, C R Maurer, D M Muratore, R L Galloway, J M Fitzpatrick.   

Abstract

This paper presents a method designed to register preoperative computed tomography (CT) images to vertebral surface points acquired intraoperatively from ultrasound (US) images or via a tracked probe. It also presents a comparison of the registration accuracy achievable with surface points acquired from the entire posterior surface of the vertebra to the accuracy achievable with points acquired only from the spinous process and central laminar regions. Using a marker-based method as a reference, this work shows that submillimetric registration accuracy can be obtained even when a small portion of the posterior vertebral surface is used for registration. It also shows that when selected surface patches are used, CT slice thickness is not a critical parameter in the registration process. Furthermore, the paper includes qualitative results of registering vertebral surface points in US images to multiple CT slices. The method has been tested with US points and physical points on a plastic spine phantom and with simulated data on a patient CT scan.

Entities:  

Mesh:

Year:  1998        PMID: 9874298     DOI: 10.1109/42.736029

Source DB:  PubMed          Journal:  IEEE Trans Med Imaging        ISSN: 0278-0062            Impact factor:   10.048


  15 in total

1.  Validation of automated ultrasound-CT registration of vertebrae.

Authors:  Charles X B Yan; Benoît Goulet; Sean Jy-Shyang Chen; Donatella Tampieri; D Louis Collins
Journal:  Int J Comput Assist Radiol Surg       Date:  2011-11-24       Impact factor: 2.924

2.  Ultrasound-CT registration of vertebrae without reconstruction.

Authors:  Charles X B Yan; Benoît Goulet; Donatella Tampieri; D Louis Collins
Journal:  Int J Comput Assist Radiol Surg       Date:  2012-06-15       Impact factor: 2.924

3.  Towards accurate, robust and practical ultrasound-CT registration of vertebrae for image-guided spine surgery.

Authors:  Charles X B Yan; Benoît Goulet; Julie Pelletier; Sean Jy-Shyang Chen; Donatella Tampieri; D Louis Collins
Journal:  Int J Comput Assist Radiol Surg       Date:  2010-10-26       Impact factor: 2.924

4.  Evaluation of achievable registration accuracy of the femur during minimally invasive total hip replacement.

Authors:  F C Popescu; M Viceconti; F Traina; A Toni
Journal:  Med Biol Eng Comput       Date:  2005-07       Impact factor: 2.602

5.  On "Evaluation of the Contribution of CAS in Combination with the Subcranial/Subfrontal Approach in Anterior Skull Base Surgery" (Skull Base 2001;11:59-76).

Authors:  Walter F Thumfart; Wolfgang Freysinger
Journal:  Skull Base       Date:  2002-02

6.  Robot-assisted primary cementless total hip arthroplasty using surface registration techniques: a short-term clinical report.

Authors:  Nobuo Nakamura; Nobuhiko Sugano; Takashi Nishii; Hidenobu Miki; Akihiro Kakimoto; Mitsuyoshi Yamamura
Journal:  Int J Comput Assist Radiol Surg       Date:  2009-02-13       Impact factor: 2.924

7.  Feasibility study for image-guided kidney surgery: assessment of required intraoperative surface for accurate physical to image space registrations.

Authors:  Anne B Benincasa; Logan W Clements; S Duke Herrell; Robert L Galloway
Journal:  Med Phys       Date:  2008-09       Impact factor: 4.071

8.  A multi-vertebrae CT to US registration of the lumbar spine in clinical data.

Authors:  Simrin Nagpal; Purang Abolmaesumi; Abtin Rasoulian; Ilker Hacihaliloglu; Tamas Ungi; Jill Osborn; Victoria A Lessoway; John Rudan; Melanie Jaeger; Robert N Rohling; Dan P Borschneck; Parvin Mousavi
Journal:  Int J Comput Assist Radiol Surg       Date:  2015-07-15       Impact factor: 2.924

9.  Generalized iterative most likely oriented-point (G-IMLOP) registration.

Authors:  Seth Billings; Russell Taylor
Journal:  Int J Comput Assist Radiol Surg       Date:  2015-05-23       Impact factor: 2.924

10.  Deep learning-based liver segmentation for fusion-guided intervention.

Authors:  Xi Fang; Sheng Xu; Bradford J Wood; Pingkun Yan
Journal:  Int J Comput Assist Radiol Surg       Date:  2020-04-21       Impact factor: 2.924

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