Multi-Coil MRI Reconstruction Challenge—Assessing Brain MRI Reconstruction Models and Their Generalizability to Varying Coil Configurations

Autor: Beauferris, Youssef, Teuwen, Jonas, Karkalousos, Dimitrios, Moriakov, Nikita, Caan, Matthan, Yiasemis, George, Rodrigues, L. via, Lopes, Alexandre, Pedrini, Helio, Rittner, Letícia, Dannecker, Maik, Studenyak, Viktor, Gröger, Fabian, Vyas, Devendra, Faghih-Roohi, Shahrooz, Kumar Jethi, Amrit, Chandra Raju, Jaya, Sivaprakasam, Mohanasankar, Lasby, Mike, Nogovitsyn, Nikita, Loos, Wallace, Frayne, Richard, Souza, Roberto
Přispěvatelé: Biomedical Engineering and Physics, Graduate School, ANS - Brain Imaging, APH - Methodology, APH - Aging & Later Life
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Frontiers in Neuroscience, 16
Frontiers in neuroscience, 16:919186. Frontiers Media S.A.
ISSN: 1662-4548
1662-453X
Popis: Contains fulltext : 283300.pdf (Publisher’s version ) (Open Access) Deep-learning-based brain magnetic resonance imaging (MRI) reconstruction methods have the potential to accelerate the MRI acquisition process. Nevertheless, the scientific community lacks appropriate benchmarks to assess the MRI reconstruction quality of high-resolution brain images, and evaluate how these proposed algorithms will behave in the presence of small, but expected data distribution shifts. The multi-coil MRI (MC-MRI) reconstruction challenge provides a benchmark that aims at addressing these issues, using a large dataset of high-resolution, three-dimensional, T1-weighted MRI scans. The challenge has two primary goals: (1) to compare different MRI reconstruction models on this dataset and (2) to assess the generalizability of these models to data acquired with a different number of receiver coils. In this paper, we describe the challenge experimental design and summarize the results of a set of baseline and state-of-the-art brain MRI reconstruction models. We provide relevant comparative information on the current MRI reconstruction state-of-the-art and highlight the challenges of obtaining generalizable models that are required prior to broader clinical adoption. The MC-MRI benchmark data, evaluation code, and current challenge leaderboard are publicly available. They provide an objective performance assessment for future developments in the field of brain MRI reconstruction.
Databáze: OpenAIRE
Externí odkaz: