Evidence map›Paper›PMID 42510500›Full record

ArticleBioengineering (Basel, Switzerland)2026

Reconstruction Accuracy vs. Discriminative Power: Spectral Unmixing Performance in Brain Tissue Hyperspectral Imaging.

Alejandro Martinez de Ternero, Alberto Martín-Pérez, Manuel Villa, Eduardo Juarez

Abstract read
In one paragraph

Article in Bioengineering (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Alejandro Martinez de TerneroCEIMM, Center for Industrial Electronics and Multimodal Systems, Universidad Politécnica de Madrid, 28031 Madrid, Spain.ORCID 0000-0003-2668-2903
Alberto Martín-PérezCEIMM, Center for Industrial Electronics and Multimodal Systems, Universidad Politécnica de Madrid, 28031 Madrid, Spain.ORCID 0000-0003-4715-6814
Manuel VillaCEIMM, Center for Industrial Electronics and Multimodal Systems, Universidad Politécnica de Madrid, 28031 Madrid, Spain.ORCID 0000-0001-7000-6289
Eduardo JuarezCEIMM, Center for Industrial Electronics and Multimodal Systems, Universidad Politécnica de Madrid, 28031 Madrid, Spain.ORCID 0000-0002-6096-1511

Funding

European Comission STRATUM - 101137416
6 · The paper itself

Abstract

Hyperspectral imaging holds promise for intraoperative brain tissue characterisation, but its high dimensionality complicates clinical deployment. Spectral unmixing offers a pathway to compress data into interpretable abundance maps, yet its impact on downstream tissue discrimination remains unclear. This study evaluated four unmixing models (ASM, LMM, PPNMM, FBM) and three normalisation strategies (SNV, L2, Max) across two hyperspectral in vivo brain surgery datasets HELICoiD (

Indexed as

brain tissueclassificationhyperspectralspectral unmix

Identifiers

PMID42510500
PMCPMC13403696

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.