A hierarchical approach to deep learning and its application to tomographic reconstruction

Lin Fu; Bruno De Man

doi:10.1117/12.2534615

28 May 2019 A hierarchical approach to deep learning and its application to tomographic reconstruction

Lin Fu, Bruno De Man

Proceedings Volume 11072, 15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine; 1107202 (2019) https://doi.org/10.1117/12.2534615
Event: Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, 2019, Philadelphia, United States

Abstract

Deep learning (DL) has been successfully applied to many image analysis and image enhancement tasks, but applying DL to inverse problems such as tomographic reconstruction remains challenging due to its high dimensionality and non-local spatial relationship. This paper introduces a hierarchical network architecture that enables purely DL-based tomographic reconstruction for full-size computed tomography (CT) datasets. The proposed method recursively decomposes the reconstruction problem into hierarchical sub problems that can each be solved by a neural network. Overall, the hierarchical approach requires exponentially fewer parameters than a generic network would, and in theory, is of lower computational order of complexity than analytical filtered-backprojection (FBP) reconstruction. As an example, we built a hierarchical network to reconstruct 2D CT images directly from sinograms without relying on conventional analytical or iterative reconstruction components. The hierarchical approach is extensible to three dimensions and to other applications such as emission and magnetic resonance reconstruction. Such DL-based reconstruction opens the door to an entirely new type of reconstruction, which could potentially lead to a better tradeoff between image quality and computational complexity.

Citation Download Citation

Lin Fu and Bruno De Man "A hierarchical approach to deep learning and its application to tomographic reconstruction", Proc. SPIE 11072, 15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, 1107202 (28 May 2019); https://doi.org/10.1117/12.2534615

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