ArticleScientific reports2022
Spectral organ fingerprints for machine learning-based intraoperative tissue classification with hyperspectral imaging in a porcine model.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 2 of them syntheses that pooled it.
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Who cites it
32 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Medical hyperspectral imaging: an updated review of technology advancements and biomedical applications.Journal of biomedical optics · 2026Pooled it
- The Advances in Computer Vision That Are Enabling More Autonomous Actions in Surgery: A Systematic Review of the Literature.Sensors (Basel, Switzerland) · 2022Pooled it
- Hyperspectral imaging as a new diagnostic tool for cervical intraepithelial neoplasia.Archives of gynecology and obstetrics · 2023Trial
- Implementation of hyperspectral imaging in a trauma resuscitation room: a randomized controlled trial.Scandinavian journal of trauma, resuscitation and emergency medicine · 2022Trial
- Hyperspectral imaging for objective microcirculatory assessment in trauma patients.Scientific reports · 2026Observational
- AI learns across species to address human clinical imaging data sparsity.Nature biomedical engineering · 2026Article
- Xeno-learning: knowledge transfer across species in deep learning-based spectral image analysis.Nature biomedical engineering · 2026Article
- Hyperspectral Fingerprints of Abdominal and Pelvic Organs.Journal of imaging · 2026Article
- Hyperspectral imaging for orthopedic surgery: lightweight AI enables real-time bone and cartilage segmentation.Medical & biological engineering & computing · 2026Article
- Learning to simulate realistic human diffuse reflectance spectra.Journal of biomedical optics · 2026Article
- Methotrexate-Loaded Liposomal Formulation Enables 6-Week Sustained Intraocular Therapeutic Drug Release in a Porcine Model.Advanced healthcare materials · 2026Article
- Hyperspectral Imaging Accurately Detects Renal Malperfusion Due to High Intrarenal Pressure.European urology open science · 2025Article
- Semantic hyperspectral image synthesis for cross-modality knowledge transfer in surgical data science.International journal of computer assisted radiology and surgery · 2025Article
- Detection of flap malperfusion after microsurgical tissue reconstruction using hyperspectral imaging and machine learning.Scientific reports · 2025Article
- Masked image modeling in medical hyperspectral imaging: reconstruction evaluation and downstream tasks.Proceedings of SPIE--the International Society for Optical Engineering · 2025Article
- RGB to hyperspectral: Spectral reconstruction for enhanced surgical imaging.Healthcare technology letters · 2024Article
- Article
- [Modern approaches and technologies to prevent anastomotic leakage in the gastrointestinal tract].Chirurgie (Heidelberg, Germany) · 2024Article
- Spectral characterization of intraoperative renal perfusion using hyperspectral imaging and artificial intelligence.Scientific reports · 2024Article
- A proof of concept for microcirculation monitoring using machine learning based hyperspectral imaging in critically ill patients: a monocentric observational study.Critical care (London, England) · 2024Observational
Corrections and comments
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Authors and funding
22 authors.
Funding
Abstract
Visual discrimination of tissue during surgery can be challenging since different tissues appear similar to the human eye. Hyperspectral imaging (HSI) removes this limitation by associating each pixel with high-dimensional spectral information. While previous work has shown its general potential to discriminate tissue, clinical translation has been limited due to the method's current lack of robustness and generalizability. Specifically, the scientific community is lacking a comprehensive spectral tissue atlas, and it is unknown whether variability in spectral reflectance is primarily explained by tissue type rather than the recorded individual or specific acquisition conditions. The contribution of this work is threefold: (1) Based on an annotated medical HSI data set (9059 images from 46 pigs), we present a tissue atlas featuring spectral fingerprints of 20 different porcine organs and tissue types. (2) Using the principle of mixed model analysis, we show that the greatest source of variability related to HSI images is the organ under observation. (3) We show that HSI-based fully-automatic tissue differentiation of 20 organ classes with deep neural networks is possible with high accuracy (> 95%). We conclude from our study that automatic tissue discrimination based on HSI data is feasible and could thus aid in intraoperative decisionmaking and pave the way for context-aware computer-assisted surgery systems and autonomous robotics.
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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.