Interactive tissue separation and visualization with dual-energy data on the GPU

Fernando Vega-Higuera; Bernhard Krauss

doi:10.1117/12.769421

17 March 2008 Interactive tissue separation and visualization with dual-energy data on the GPU

Fernando Vega-Higuera, Bernhard Krauss

Proceedings Volume 6918, Medical Imaging 2008: Visualization, Image-Guided Procedures, and Modeling; 69182Z (2008) https://doi.org/10.1117/12.769421
Event: Medical Imaging, 2008, San Diego, California, United States

Abstract

Dual-Energy CT makes it possible to separate contributions of different X-ray attenuation processes or materials in the CT image. Thereby, standard Dual-Energy tissue classification techniques perform a so called material analysis or decomposition. The resulting material maps can then be used to perform explicit segmentation of anatomical structures such as osseous tissue in case of bone removal. As a drawback, information about tissue classes included in the scan must be known beforehand in order to choose the appropriate material analysis algorithms. We propose direct volume rendering with bidimensional transfer functions as a tool for interactive and intuitive exploration of Dual-Energy scans. Thereby, adequate visualization of the Dual-Energy histogram provides the basis for easily identifying different tissue classes. Transfer functions are interactively adjusted over the Dual-Energy histogram where the x- and y-axis correspond to the 80 kV and 140kV intensities respectively. GPU implementation allows precise fine-tuning of transfer functions with real time feedback in the resulting visualization. Additionally, per fragment filtering and post interpolative Dual-Energy tissue classification are provided. Moreover, interactive histogram exploration makes it possible to create adequate Dual-Energy visualizations without pre-processing or previous knowledge about existing tissue classes.

Citation Download Citation

Fernando Vega-Higuera and Bernhard Krauss "Interactive tissue separation and visualization with dual-energy data on the GPU", Proc. SPIE 6918, Medical Imaging 2008: Visualization, Image-Guided Procedures, and Modeling, 69182Z (17 March 2008); https://doi.org/10.1117/12.769421

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available