ArticleScientific data2025
SLIMBRAIN database: A multimodal image database of in vivo human brains for tumour detection.
Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Hyperspectral imaging for tumor resection guidance in surgery: a systematic review of preclinical and clinical studies.Journal of biomedical optics · 2025Pooled it
- Reconstruction Accuracy vs. Discriminative Power: Spectral Unmixing Performance in Brain Tissue Hyperspectral Imaging.Bioengineering (Basel, Switzerland) · 2026Article
- High-to-Low Spectral Mapping for Cross-System Feature Adaptation in Medical Hyperspectral Imaging.Bioengineering (Basel, Switzerland) · 2026Article
- Improving Brain Tumor Detection by Cortical Surface and Vessels Segmentation Through RGB-to-HSI Transfer Learning.Cancers · 2026Article
- Article
- In-vivo optical properties spectra across five body locations on ten subjects using time-domain diffuse optics.Scientific data · 2026Article
- SLIMBRAIN database: A multimodal image database of in vivo human brains for tumour detection.Scientific data · 2025Article
- Hyperspectral imaging in neurosurgery: a review of systems, computational methods, and clinical applications.Journal of biomedical optics · 2025Review
- Spectral analysis comparison of pushbroom and snapshot hyperspectral cameras forJournal of biomedical optics · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors.
Funding
Abstract
Hyperspectral imaging (HSI) and machine learning (ML) have been employed in the medical field for classifying highly infiltrative brain tumours. Although existing HSI databases of in vivo human brains are available, they present two main deficiencies. First, the amount of labelled data are scarce, and second, 3D-tissue information is unavailable. To address both issues, we present the SLIMBRAIN database, a multimodal image database of in vivo human brains that provides HS brain tissue data within the 400-1000 nm spectra, as well as RGB, depth and multiview images. Two HS cameras, two depth cameras and different RGB sensors were used to capture images and videos from 193 patients. All the data in the SLIMBRAIN database can be used in a variety of ways, for example, to train ML models with more than 1 million HS pixels available and labelled by neurosurgeons, to reconstruct 3D scenes or to visualize RGB brain images with different pathologies, offering unprecedented flexibility for both the medical and engineering communities.
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.