ArticleVisual computing for industry, biomedicine, and art2026
MEDI-SLATE: medical imaging slide-lecture aligned teaching ensemble.
Article in Visual computing for industry, biomedicine, and art, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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Authors and funding
3 authors.
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Abstract
Slide-based lectures remain the primary means by which undergraduate students learn about the mathematical, physical, and systems-level foundations of medical imaging. However, despite their central educational role, no openly available dataset pairs imaging lecture slides with clean, well-aligned explanatory narration suitable for scientific and educational research. The authors introduced MEDI-SLATE: medical imaging slide-lecture aligned teaching ensemble, constructed from a complete undergraduate biomedical engineering medical imaging course. The dataset contains 1117 high-resolution slides paired with refined narration derived from classroom audio through automatic speech recognition, followed by careful manual cleanup. MEDI-SLATE encompasses linear systems, Fourier analysis, signal processing, X-ray physics, computed tomography, positron emission tomography/single photon emission computed tomography, magnetic resonance imaging , ultrasound, and optical imaging. In addition to the slide-text pairs, the dataset includes lecture-level difficulty tags, key ideas, common student misunderstandings, and practice questions sourced directly from the instructor's materials. A fully reproducible preprocessing pipeline covering slide extraction, narration refinement, alignment, and corpus-level analyses is provided. MEDI-SLATE offers a high-fidelity, openly available resource for medical imaging education, curriculum development, multimodal learning research, and creation of artificial intelligence-assisted instructional tools, with all data and codes released for transparent use and future extension.
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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.