ArticleMedical physics2025
Report on the quantitative intra-voxel incoherent motion diffusion MRI reconstruction grand challenge.
Article in Medical physics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
purposeThe 2024 quantitative intra-voxel incoherent motion diffusion MRI (IVIM-dMRI) reconstruction grand challenge aimed to benchmark and advance reconstruction algorithms for extracting quantitative tissue parameters from diffusion MRI (dMRI) data. Focusing on the IVIM model, the challenge aimed to improve the accuracy and robustness of clinical parameter estimation, addressing key barriers to broader clinical adoption.
methodsParticipants were tasked with reconstructing fractional perfusion, pseudo-diffusion coefficient, and true diffusion coefficient from simulated
resultsThe challenge attracted 42 teams from six countries, with seven progressing to the final phase. The rRMSE ranged in [0.0345, 1.24]. The top-performing algorithm employed a cascaded U-Net architecture for image denoising and parameter fitting. Overall, the competition highlighted the potential of advanced methodologies, particularly DL, in addressing complex inverse problems in medical imaging.
conclusionThe IVIM-dMRI grand challenge demonstrated significant advancements in the accuracy and robustness of dMRI reconstruction. Although the simulation-based approach provided a controlled environment, future efforts must address real-world complexities to ensure clinical applicability.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.