ReviewInternational journal of computer assisted radiology and surgery2016
Hyperspectral interventional imaging for enhanced tissue visualization and discrimination combining band selection methods.
Review in International journal of computer assisted radiology and surgery, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04589884 (Intraoperative EXamination Using MAChine-learning-based HYperspectral for diagNosis & Autonomous Anatomy Assessment), which is not on this map. Cited by 17 papers, 3 of them syntheses that pooled it.
What it found
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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.
Intraoperative EXamination Using MAChine-learning-based HYperspectral for diagNosis & Autonomous Anatomy Assessment
Who cites it
17 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Medical hyperspectral imaging: an updated review of technology advancements and biomedical applications.Journal of biomedical optics · 2026Pooled it
- Hyperspectral Imaging and the Retina: Worth the Wave?Translational vision science & technology · 2020Pooled it
- Intraoperative multispectral and hyperspectral label-free imaging: A systematic review of in vivo clinical studies.Journal of biophotonics · 2019Pooled it
- Perspective on the current state of hyperspectral/multispectral imaging for minimally invasive surgery.Journal of biomedical optics · 2026Review
- Targeted multispectral filter array design for the optimization of endoscopic cancer detection in the gastrointestinal tract.Journal of biomedical optics · 2024Article
- Compact and ultracompact spectral imagers: technology and applications in biomedical imaging.Journal of biomedical optics · 2023Review
- In vitro hyperspectral analysis of tattoo dyes.Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI) · 2023Article
- Band selection for oxygenation estimation with multispectral/hyperspectral imaging.Biomedical optics express · 2022Article
- Intraoperative Guidance Using Hyperspectral Imaging: A Review for Surgeons.Diagnostics (Basel, Switzerland) · 2021Review
- Wound Size Imaging: Ready for Smart Assessment and Monitoring.Advances in wound care · 2021Article
- Deep Learning Analysis of In Vivo Hyperspectral Images for Automated Intraoperative Nerve Detection.Diagnostics (Basel, Switzerland) · 2021Article
- Explainable liver tumor delineation in surgical specimens using hyperspectral imaging and deep learning.Biomedical optics express · 2021Article
- Shortwave infrared otoscopy for diagnosis of middle ear effusions: a machine-learning-based approach.Scientific reports · 2021Article
- Pose estimation of a markerless fiber bundle for endoscopic optical biopsy.Journal of medical imaging (Bellingham, Wash.) · 2021Article
- Laparoscopic system for simultaneous high-resolution video and rapid hyperspectral imaging in the visible and near-infrared spectral range.Journal of biomedical optics · 2020Article
- Spectrally Tunable Neural Network-Assisted Segmentation of Microneurosurgical Anatomy.Frontiers in neuroscience · 2020Article
- Uncertainty-aware performance assessment of optical imaging modalities with invertible neural networks.International journal of computer assisted radiology and surgery · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeHyperspectral imaging is an emerging technology recently introduced in medical applications inasmuch as it provides a powerful tool for noninvasive tissue characterization. In this context, a new system was designed to be easily integrated in the operating room in order to detect anatomical tissues hardly noticed by the surgeon's naked eye.
methodOur LCTF-based spectral imaging system is operative over visible, near- and middle-infrared spectral ranges (400-1700 nm). It is dedicated to enhance critical biological tissues such as the ureter and the facial nerve. We aim to find the best three relevant bands to create a RGB image to display during the intervention with maximal contrast between the target tissue and its surroundings. A comparative study is carried out between band selection methods and band transformation methods. Combined band selection methods are proposed. All methods are compared using different evaluation criteria.
resultsExperimental results show that the proposed combined band selection methods provide the best performance with rich information, high tissue separability and short computational time. These methods yield a significant discrimination between biological tissues.
conclusionWe developed a hyperspectral imaging system in order to enhance some biological tissue visualization. The proposed methods provided an acceptable trade-off between the evaluation criteria especially in SWIR spectral band that outperforms the naked eye's capacities.
Indexed as
Identifiers
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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.