A variational approach for reconstructing low dose images in clinical helical CT

Authors:
Synho Do;W. Clem Karl;Mannudeep K. Kalra;Thomas J. Brady;Homer Pien
Affiliations:
Massachusetts General Hospital and Harvard Medical School, Dept. of Radiology, Boston, MA;Boston University, Dept. of Electrical and Computer Engineering, Boston, MA;Massachusetts General Hospital and Harvard Medical School, Dept. of Radiology, Boston, MA;Massachusetts General Hospital and Harvard Medical School, Dept. of Radiology, Boston, MA;Massachusetts General Hospital and Harvard Medical School, Dept. of Radiology, Boston, MA
Venue:
ISBI'10 Proceedings of the 2010 IEEE international conference on Biomedical imaging: from nano to Macro
Year:
2010

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Abstract

Exposure to medical radiation is an important healthcare concern. In this paper we present a variational formulation for image reconstruction from low-dose transmission X-ray CT as well as its application to real clinical data. Our projection domain reconstruction method is based on high-order total variation penalties. We apply the method to clinical neck data obtained from a current 64-channel MDCT helical scanner, where small features and large dynamic range variation are pervasive. The ability to generate high-quality images even at 75% dose reduction is demonstrated. In particular, our approach exhibits image SNR comparable to full-dose filtered backprojection images while avoiding the obvious stair case and blockiness artifacts typically encountered in such methods.