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1000
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Abstract/Summary
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<jats:title>Abstract</jats:title>
<jats:sec>
<jats:title>Purpose</jats:title>
<jats:p>A prototype infrared camera – cone-beam computed tomography (CBCT) system for tracking in brachytherapy has recently been developed. We evaluated for the first time the corresponding tracking accuracy and uncertainties, and implemented a tracking-based prediction of needles on CBCT scans.</jats:p>
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<jats:title>Methods</jats:title>
<jats:p>A marker tool rigidly attached to needles was 3D printed. The precision and accuracy of tool tracking was then evaluated for both static and dynamic scenarios. Euclidean distances between the tracked and CBCT-derived markers were assessed as well. To implement needle tracking, ground truth models of the tool attached to 200 mm and 160 mm needles were matched to the tracked positions in order to project the needles into CBCT scans. Deviations between projected and actual needle tips were measured. Finally, we put our results into perspective with simulations of the system’s tracking uncertainties.</jats:p>
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<jats:title>Results</jats:title>
<jats:p>For the stationary scenario and dynamic movements, we achieved tool-tracking precision and accuracy of 0.04 ± 0.06 mm and 0.16 ± 0.18 mm, respectively. The tracked marker positions differed by 0.52 ± 0.18 mm from the positions determined via CBCT. In addition, the predicted needle tips in air deviated from the actual tip positions by only 1.62 ± 0.68 mm (200 mm needle) and 1.49 ± 0.62 mm (160 mm needle). The simulated tracking uncertainties resulted in tip variations of 1.58 ± 0.91 mm and 1.31 ± 0.69 mm for the 200 mm and 160 mm needles, respectively.</jats:p>
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<jats:sec>
<jats:title>Conclusion</jats:title>
<jats:p>With the innovative system it was possible to achieve a high tracking and prediction accuracy of marker tool and needles. The system shows high potential for applicator tracking in brachytherapy.</jats:p>
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1000
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Hinweis
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DeepGreen-ID: df1ce008da424ffcbe5e06fef1d1da64 ; metadata provieded by: DeepGreen (https://www.oa-deepgreen.de/api/v1/), LIVIVO search scope life sciences (http://z3950.zbmed.de:6210/livivo), Crossref Unified Resource API (https://api.crossref.org/swagger-ui/index.html), to.science.api (https://frl.publisso.de/), ZDB JSON-API (beta) (https://zeitschriftendatenbank.de/api/), lobid - Dateninfrastruktur für Bibliotheken (https://lobid.org/resources/search)
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