{"url":"/dataset/mtneuro","name":"MTNeuro","full_name":null,"description_markdown":"**MTNeuro** is a multi-task neuroimaging benchmark built on volumetric, micrometer-resolution X-ray microtomography images spanning a large thalamocortical section of mouse brain, encompassing multiple cortical and subcortical regions.\r\n\r\nThis dataset provides some key features for the neuroinformatics processing community:\r\n\r\n- Three Dimensional Multi-Scale Annotated Dataset: The 3D x-ray microtomography dataset spans multiple brain areas and includes region of interest (ROI) annotations, densely annotated 3D cutouts, and semantic interpretable features.\r\n\r\n- Multi-Level Benchmark Tasks: Benchmark tasks feature both microscopic and macroscopic classification objectives.\r\n\r\n- Evaluation of Model Baselines: Both 2D and 3D training regimes are considered when training supervised and unsupervised models.\r\n\r\nThe data are derived from a unique 3D X-ray microtomography dataset covering areas of mouse cortex and thalamus. At 1.17um isotropic resolution for each voxel, both microsctructure (blood vessels, cell bodies, white matter) and macrostructure labels are available.\r\n\r\nSource: [MTNeuro: A Benchmark for Evaluating Representations of Brain Structure Across Multiple Levels of Abstraction](https://arxiv.org/pdf/2301.00345v1.pdf)\r\n\r\nImage Source: [https://github.com/mtneuro/mtneuro](https://github.com/mtneuro/mtneuro)","description_withheld":null,"homepage":"https://github.com/mtneuro/mtneuro","introduced_date":"2023-01-01","introduced_date_note":null,"introduced_by":{"paper":"/paper/mtneuro-a-benchmark-for-evaluating","title":"MTNeuro: A Benchmark for Evaluating Representations of Brain Structure Across Multiple Levels of Abstraction","first_author":"Jorge Quesada","url":null},"license":{"name":"MIT License","url":"https://github.com/MTNeuro/MTNeuro/blob/main/LICENSE.md"},"modalities":[{"name":"3D","url":"/datasets/modality/3d"},{"name":"Medical","url":"/datasets/modality/medical"}],"tasks":[{"name":"Semantic Segmentation","url":"/task/semantic-segmentation","datasets_with_task":"/datasets/task/semantic-segmentation"}],"languages":[],"variants":["MTNeuro"],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}