Joint synthesis of WMn MPRAGE and parameter maps using deep learning and an imaging equation

Pouria Tohidi; Shuo Han; Lianrui Zuo; Jiachen Zhuo; Steven R. Roys; Aaron Carass; Rao P. Gullapalli; Jerry L. Prince

doi:10.1117/12.2653988

3 April 2023 Joint synthesis of WMn MPRAGE and parameter maps using deep learning and an imaging equation

Pouria Tohidi, Shuo Han, Lianrui Zuo, Jiachen Zhuo, Steven R. Roys, Aaron Carass, Rao P. Gullapalli, Jerry L. Prince

Proceedings Volume 12464, Medical Imaging 2023: Image Processing; 124642F (2023) https://doi.org/10.1117/12.2653988
Event: SPIE Medical Imaging, 2023, San Diego, California, United States

Conference Poster

Abstract

T1-weighted (T1w) magnetic resonance (MR) neuroimages are usually acquired with an inversion time that nulls the cerebrospinal fluid—i.e., CSFn MPRAGE images—but are rarely acquired with the white matter nulled—i.e., WMn images. Since WMn images can be useful in highlighting thalamic nuclei, we develop a method to synthesize these images from other images that are often acquired. We propose a two-part model, with a deep learning based encoder and a decoder based on an imaging equation which governs the acquisition of our T1w images. This model can be trained on a subset of the dataset where the WMn MPRAGE images are available. Our model takes image contrasts that are often acquired (e.g., CSFn MPRAGE) as input, and generates WMn MPRAGE images as output, along with two quantitative parameter maps as intermediate results. After training, our model is able to generate a synthetic WMn MPRAGE image for any given subject. Our model results have high signal-to-noise ratio and are visually almost identical to the ground truth images. Furthermore, downstream thalamic nuclei segmentation on synthetic WMn MPRAGE images are consistent with ground truth WMn MPRAGE images.

Citation Download Citation

Pouria Tohidi, Shuo Han, Lianrui Zuo, Jiachen Zhuo, Steven R. Roys, Aaron Carass, Rao P. Gullapalli, and Jerry L. Prince "Joint synthesis of WMn MPRAGE and parameter maps using deep learning and an imaging equation", Proc. SPIE 12464, Medical Imaging 2023: Image Processing, 124642F (3 April 2023); https://doi.org/10.1117/12.2653988

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