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Visualisation of Ultrasound Computer Tomography Breast Dataset

Jerome, Nicholas Tan; Ateyev, Zhassulan; Lebedev, Vladislav; Hopp, Torsten ORCID iD icon; Zapf, Michael; Chilingaryan, Suren ORCID iD icon; Kopmann, Andreas ORCID iD icon

Abstract:

Medical visualisation plays a vital role in diagnosing and detecting early symptoms. In particular, visualising the anatomy of breast model allows doctors or practitioners to identify first signs of the breast cancer. However, despite the advancement in visualisation techniques, most standard visualisation approaches in the medical field still rely on analysing 2D images which lack spatial information. In this paper, we present an interactive web-based 3D visualisation tool for ultrasound computer tomography (USCT) breast dataset. We base our implementation on the Web-based Graphics Language (WebGL) technology that utilises the GPU parallel architecture. The tool serves as a common platform among research collaborators to analyse
and share findings on their dataset. We render the data using state-of-the-art algorithms of interactive computer graphics and produce results with quality comparable to the desktop application. Aside from that, our tool enables researchers to perform arbitrary view slicing, modality thresholding and multiple rendering modes. In the evaluation, our tool maintains an interactive frame rate above 30 fps on a standard desktop.


Verlagsausgabe §
DOI: 10.5445/IR/1000080283
Veröffentlicht am 05.10.2018
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Prozessdatenverarbeitung und Elektronik (IPE)
Institut für Technik der Informationsverarbeitung (ITIV)
Publikationstyp Proceedingsbeitrag
Publikationsjahr 2017
Sprache Englisch
Identifikator ISBN: 978-3-7315-0689-8
urn:nbn:de:swb:90-802833
KITopen-ID: 1000080283
HGF-Programm 54.02.02 (POF III, LK 01) Ultraschnelle Datenauswertung
Erschienen in Proceedings of the International Workshop on Medical Ultrasound Tomography: 1.- 3. Nov. 2017, Speyer, Germany. Hrsg.: T. Hopp
Veranstaltung 1st International Workshop on Medical Ultrasound Tomography (MUST 2017), Speyer, Deutschland, 01.11.2017 – 03.11.2017
Verlag KIT Scientific Publishing
Seiten 349-359
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