Int J Med Robot - A study on the theoretical and practical accuracy of conoscopic holography-based surface measurements: toward image registration in minimally invasive surgery.

Tópicos

{ imag(1057) registr(996) error(939) }
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Resumo

CKGROUND: Registered medical images can assist with surgical navigation and enable image-guided therapy delivery. In soft tissues, surface-based registration is often used and can be facilitated by laser surface scanning. Tracked conoscopic holography (which provides distance measurements) has been recently proposed as a minimally invasive way to obtain surface scans. Moving this technique from concept to clinical use requires a rigorous accuracy evaluation, which is the purpose of our paper.METHODS: We adapt recent non-homogeneous and anisotropic point-based registration results to provide a theoretical framework for predicting the accuracy of tracked distance measurement systems. Experiments are conducted a complex objects of defined geometry, an anthropomorphic kidney phantom and a human cadaver kidney.RESULTS: Experiments agree with model predictions, producing point RMS errors consistently<1 mm, surface-based registration with mean closest point error<1 mm in the phantom and a RMS target registration error of 0.8 mm in the human cadaver kidney.CONCLUSIONS: Tracked conoscopic holography is clinically viable; it enables minimally invasive surface scan accuracy comparable to current clinical methods that require open surgery.

Resumo Limpo

ckground regist medic imag can assist surgic navig enabl imageguid therapi deliveri soft tissu surfacebas registr often use can facilit laser surfac scan track conoscop holographi provid distanc measur recent propos minim invas way obtain surfac scan move techniqu concept clinic use requir rigor accuraci evalu purpos papermethod adapt recent nonhomogen anisotrop pointbas registr result provid theoret framework predict accuraci track distanc measur system experi conduct complex object defin geometri anthropomorph kidney phantom human cadav kidneyresult experi agre model predict produc point rms error consist mm surfacebas registr mean closest point error mm phantom rms target registr error mm human cadav kidneyconclus track conoscop holographi clinic viabl enabl minim invas surfac scan accuraci compar current clinic method requir open surgeri

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