Ultra-fast-pitch acquisition and reconstruction in helical CT

Hao Gong; Liqiang Ren; Cynthia H. McCollough; Lifeng Yu

doi:10.1117/12.2549315

16 March 2020 Ultra-fast-pitch acquisition and reconstruction in helical CT

Hao Gong, Liqiang Ren, Cynthia H. McCollough, Lifeng Yu

Author Affiliations +

Proceedings Volume 11312, Medical Imaging 2020: Physics of Medical Imaging; 1131209 (2020) https://doi.org/10.1117/12.2549315
Event: SPIE Medical Imaging, 2020, Houston, Texas, United States

Abstract

A fast scan with a high helical pitch is desirable for many CT exams, such as pediatric, chest, and some of cardiovascular exams, to suppress patient motion artifacts. However, on a single-source scanner, the pitch typically cannot exceed ~1.5 without generating image distortion within the entire scanning field of view due to insufficient data acquired in a fast pitch mode. In this work, we developed a deep convolutional neural network-based approach to reducing artifacts on images reconstructed from insufficient data acquired in an ultra-fast-pitch mode (𝑝𝑝 ≥ 2.0). This custom-designed neural network, referred to as Ultra-fast-pitch image reconstruction neural network (UFP-net) consists of functional modules using both local and non-local operators, as well as the z-coordinate of each image, to effectively suppress the location- and structure-dependent artifacts induced by the fast-pitch mode. The UFP-net was trained using a customized loss function that involves image-gradient-correlation loss and feature reconstruction loss. Projection data at a regular pitch (𝑝𝑝 = 1.0) and a fast-pitch (𝑝𝑝 = 3.0) were simulated using 10 patient CT cases to generate training and validation datasets. Compared to filtered-back-projection (FBP), the UFP-net largely suppressed image artifacts and restored anatomical details. The structural similarity index (SSIM) was significantly improved (Mean SSIM: UFP-net 0.9, FBP 0.6), and the root-mean-square-error (RMSE) was largely reduced (Mean RMSE: UFP-net 57 HU, FBP 273 HU). The proposed method has the potential to enable ultra-fast-pitch data acquisition on single-source CT scanners to improve scanning speed while maintaining image quality.

Citation Download Citation

Hao Gong, Liqiang Ren, Cynthia H. McCollough, and Lifeng Yu "Ultra-fast-pitch acquisition and reconstruction in helical CT", Proc. SPIE 11312, Medical Imaging 2020: Physics of Medical Imaging, 1131209 (16 March 2020); https://doi.org/10.1117/12.2549315

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