Evidence map›Paper›PMID 41867475›Full record

SynthesisJournal of biomedical optics2026

Medical hyperspectral imaging: an updated review of technology advancements and biomedical applications.

Minh H Tran, Ling Ma, Mandy Yuan, Baowei Fei

Abstract readSystematic Review
In one paragraph

Synthesis in Journal of biomedical optics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Review
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.

Minh H TranUniversity of Texas at Dallas, Center for Imaging and Surgical Innovation, Richardson, Texas, United States.ORCID https://orcid.org/0000-0002-9936-9654
Ling MaUniversity of Texas at Dallas, Center for Imaging and Surgical Innovation, Richardson, Texas, United States.ORCID https://orcid.org/0000-0002-4352-5697
Mandy YuanUniversity of Texas at Dallas, Center for Imaging and Surgical Innovation, Richardson, Texas, United States.
Baowei FeiUniversity of Texas at Dallas, Center for Imaging and Surgical Innovation, Richardson, Texas, United States.ORCID https://orcid.org/0000-0002-9123-9484

Funding

A Real-Time Hyperspectral Laparoscopic Stereo Imaging System for Robot-Assisted SurgeryR01CA288379 · NCI · UNIVERSITY OF TEXAS DALLAS · PI BAOWEI FEI · 2024 to 2026
$1.6M
NCI NIH HHS R01 CA288379
6 · The paper itself

Abstract

Significance: Hyperspectral imaging (HSI) is an advanced spectral imaging technique that captures spatial and spectral information across numerous wavelength bands. This capability allows tissue characterization, disease detection and diagnosis, surgical guidance, and digital histopathology, making it an increasingly valuable tool with wide biological and medical applications. Aim: We aim to provide readers with (1) an understanding of the principles and technological advancements in HSI, (2) a comprehensive overview of HSI data processing and analysis methods, and (3) an updated survey of biomedical applications, from disease detection, intraoperative imaging, to histopathology. Approach: A systematic literature search was conducted using PubMed and Google Scholar with the keyword "hyperspectral imaging." We previously published a comprehensive review paper on medical HSI in 2014, which was widely cited in the field. Therefore, this updated review focused on new technology advancements and emerging applications. Based on their biological and medical relevance, 612 HSI papers were included and analyzed in this review. Results: Recent advances in HSI span both hardware and computational techniques, including improvements in sensor technology, data processing and analysis, short-wave near-infrared imaging, and deep-learning and AI tools. HSI is actively explored for various applications in oncology, neurology, ophthalmology, dermatology, cardiology, gastroenterology, hepatology, wound care, endocrinology, dentistry, infectious disease, plastic and reconstructive surgery, general surgery, intraoperative guidance, histopathology, microbiology, nanopathology, and pharmacology. Conclusions: HSI has become an emerging imaging modality in biomedical research and clinical settings. Continued advancements in hardware miniaturization, computational efficiency, and clinical validation will further solidify the role of next-generation HSI in biomedicine.

Indexed as

Hyperspectral ImagingImage Processing, Computer-AssistedAnimalsHumanscancer detectiondeep learningdisease diagnosisimage analysisintraoperative image guidancemachine learningmedical hyperspectral imagingoptical imagingpathologyspectral imaging

Identifiers

PMID41867475
PMCPMC13003176

What OpenQuestion holds

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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.