Document Detail

Towards Detection and Localization of Instruments in Minimally Invasive Surgery.
MedLine Citation:
PMID:  23192482     Owner:  NLM     Status:  Publisher    
Methods for detecting and localising surgical instruments in laparoscopic images are an important element of advanced robotic and computer assisted interventions. Robotic joint encoders and sensors integrated or mounted on the instrument can provide information about the tools position but this often has inaccuracy when transferred to the surgeons point of view. Vision sensors are currently a promising approach for determining the position of instruments in the coordinate frame of the surgical camera. In this study, we propose a vision algorithm for localising the instruments pose in 3D leaving only rotation in the axis of the tools shaft as an ambiguity.We propose a probabilistic supervised classification method to detect pixels in laparoscopic images that belong to surgical tools. We then use the classifier output to initialise an energy minimisation algorithm for estimating the pose of a prior 3D model of the instrument within a level set framework. We show that the proposed method is robust against noise using simulated data and we perform quantitative validation of the algorithm compared to ground truth obtained using an optical tracker. Finally, we demonstrate the practical application of the technique on in vivo data from MIS with traditional laparoscopic and robotic instruments.
M Allan; S Ourselin; S Thompson; D Hawkes; J Kelly; D Stoyanov
Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2012-11-21
Journal Detail:
Title:  IEEE transactions on bio-medical engineering     Volume:  -     ISSN:  1558-2531     ISO Abbreviation:  IEEE Trans Biomed Eng     Publication Date:  2012 Nov 
Date Detail:
Created Date:  2012-11-29     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  0012737     Medline TA:  IEEE Trans Biomed Eng     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine

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