Diagnostic value of sparse sampling computed tomography for radiation dose reduction: initial results

Felix K. Kopp; Rolf Bippus; Andreas P. Sauter; Daniela Muenzel; Frank Bergner; Kai Mei; Julia Dangelmaier; Benedikt J. Schwaiger; Marco Catalano; Alexander A. Fingerle; Ernst J. Rummeny; Peter B. Noël

doi:10.1117/12.2293529

9 March 2018 Diagnostic value of sparse sampling computed tomography for radiation dose reduction: initial results

Felix K. Kopp, Rolf Bippus, Andreas P. Sauter, Daniela Muenzel, Frank Bergner, Kai Mei, Julia Dangelmaier, Benedikt J. Schwaiger, Marco Catalano, Alexander A. Fingerle, Ernst J. Rummeny, Peter B. Noël

Author Affiliations +

Proceedings Volume 10573, Medical Imaging 2018: Physics of Medical Imaging; 1057340 (2018) https://doi.org/10.1117/12.2293529
Event: SPIE Medical Imaging, 2018, Houston, Texas, United States

Abstract

Computed Tomography (CT) is one of the most important imaging modalities in the medical domain. Ongoing demand for reduction of the X-ray radiation dose and advanced reconstruction algorithms induce ultra-low dose CT acquisitions more and more. However, though advanced reconstructions lead to improved image quality, the ratio between electronic detector noise and incoming signal decreases in ultra-low dose scans causing a degradation of the image quality and, therefore, building a boundary for radiation dose reduction. Future generations of CT scanners may allow sparse sampled data acquisitions, where the source can be switched on and off at any source position. Sparse sampled CT acquisitions could reduce photon starvation in ultra-low dose scans by distributing the energy of skipped projections to the remaining ones. In this work, we simulated sparse sampled CT acquisitions from clinical projection raw data and evaluated the diagnostic value of the reconstructions compared to conventional CT. Therefore, we simulated radiation dose reduction with different degrees of sparse sampling and with a tube current simulator. Up to four experienced radiologists rated the diagnostic quality of each dataset. By a dose reduction to 25% of the clinical dosage, images generated with 4-times sparse sampling – meaning a gap of three projections between two sampling positions – were consistently rated as diagnostic, while about 20% of the ratings for conventional CT were non-diagnostic. Therefore, our data give an initial indication that with sparse sampling a reduction to 25% of the clinical dose is feasible without loss of diagnostic value.

Citation Download Citation

Felix K. Kopp, Rolf Bippus, Andreas P. Sauter, Daniela Muenzel, Frank Bergner, Kai Mei, Julia Dangelmaier, Benedikt J. Schwaiger, Marco Catalano, Alexander A. Fingerle, Ernst J. Rummeny, and Peter B. Noël "Diagnostic value of sparse sampling computed tomography for radiation dose reduction: initial results", Proc. SPIE 10573, Medical Imaging 2018: Physics of Medical Imaging, 1057340 (9 March 2018); https://doi.org/10.1117/12.2293529

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