Enabling Ultra-Fast Cardiovascular Imaging Across Heterogeneous Clinical Environments with a Generalist Foundation Model and Multimodal Database
Paper • 2512.21652 • Published
Datasets:
Dataset Viewer
The dataset viewer is not available for this subset.
Cannot get the split names for the config 'default' of the dataset.
Exception: SplitsNotFoundError
Message: The split names could not be parsed from the dataset config.
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
for split_generator in builder._split_generators(
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 82, in _split_generators
raise ValueError(
ValueError: The TAR archives of the dataset should be in WebDataset format, but the files in the archive don't share the same prefix or the same types.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 65, in compute_split_names_from_streaming_response
for split in get_dataset_split_names(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
info = get_dataset_config_info(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 291, in get_dataset_config_info
raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
🚀 This repository is currently under construction. The full database is still being uploaded and will be available in the coming days!
🤗 Thank you for your interest in the MMCMR-427K database and CardioMM framework!
Motivation: Multimodal cardiovascular magnetic resonance (CMR) imaging offers comprehensive and non-invasive insights into cardiovascular disease (CVD) diagnosis and underlying mechanisms, but its widespread real-world adoption remains constrained by prolonged scan times and heterogeneity across medical environments. This underscores the urgent need to address a largely unexplored gap: a generalist reconstruction foundation model for ultra-fast CMR imaging—one capable of adapting across diverse imaging scenarios and serving as the essential substrate for all downstream analyses.
Database: To enable this goal, we curate MMCMR-427K, the largest and most comprehensive multimodal CMR k-space database to date. It comprises 427,465 multi-coil k-space data paired with structured metadata, from 6,120 scans of 1,504 participants, spanning 13 international centers (four public repositories and nine clinical centers), 15 scanners (four vendors from low-field to ultra-high-field strengths), 12 CMR modalities, and 17 CVD categories across three populations (Asian, European, and North American).
Engagement: Remarkably, in our organized CMRxRecon challenge series (2023–2025), more than 11,000 active participants from 125 countries and regions have engaged, reflecting the broad and growing global interest in next-generation CMR technologies.
Official Website: https://github.com/wangziblake/CardioMM_MMCMR-427K
Relevant Paper: https://arxiv.org/abs/2512.21652
⚠️ Very Important: File merging and integrity verification
Please strictly follow the steps below to merge and verify the dataset files. If the split files are not merged correctly, the final .tar.gz file will be corrupted and cannot be extracted successfully.
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