ArticleJournal of biomedical optics2014
Spectral-spatial classification for noninvasive cancer detection using hyperspectral imaging.
Article in Journal of biomedical optics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers, 2 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
49 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
- Hyperspectral imaging for tumor resection guidance in surgery: a systematic review of preclinical and clinical studies.Journal of biomedical optics · 2025Pooled it
- Label-free classification of nanoscale drug delivery systems using hyperspectral imaging and convolutional neural networks.International journal of pharmaceutics · 2025Article
- Development of a digital micromirror device-based hyperspectral imaging system with dynamically adjustable measurement regions.Scientific reports · 2025Article
- Endoscopic Hyperspectral Imaging System to Discriminate Tissue Characteristics in Tissue Phantom and Orthotopic Mouse Pancreatic Tumor Model.Bioengineering (Basel, Switzerland) · 2024Article
- Colon Disease Diagnosis with Convolutional Neural Network and Grasshopper Optimization Algorithm.Diagnostics (Basel, Switzerland) · 2023Article
- Detection of Oxacillin/Cefoxitin Resistance inMicroorganisms · 2023Article
- Deep Learning in Medical Hyperspectral Images: A Review.Sensors (Basel, Switzerland) · 2022Review
- Comparison of preprocessing techniques to reduce nontissue-related variations in hyperspectral reflectance imaging.Journal of biomedical optics · 2022Article
- Design and Validation of a Custom-Made Laboratory Hyperspectral Imaging System for Biomedical Applications Using a Broadband LED Light Source.Sensors (Basel, Switzerland) · 2022Article
- New Intraoperative Imaging Tools and Image-Guided Surgery in Gastric Cancer Surgery.Diagnostics (Basel, Switzerland) · 2022Review
- Hyperspectral Image Analysis of Colon Tissue and Deep Learning for Characterization of Health care.Journal of environmental and public health · 2022Article
- Pixel-level Tumor Margin Assessment of Surgical Specimen with Hyperspectral Imaging and Deep Learning Classification.Proceedings of SPIE--the International Society for Optical Engineering · 2021Article
- Article
- Deep Machine Learning for Oral Cancer: From Precise Diagnosis to Precision Medicine.Frontiers in oral health · 2021Article
- Distinction of surgically resected gastrointestinal stromal tumor by near-infrared hyperspectral imaging.Scientific reports · 2020Article
- Use of Fluorescent Dyes in Endoscopy and Diagnostic Investigation.Visceral medicine · 2020Review
- Deep learning applied to hyperspectral endoscopy for online spectral classification.Scientific reports · 2020Article
- Article
- Applications of hyperspectral imaging in the detection and diagnosis of solid tumors.Translational cancer research · 2020Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Early detection of malignant lesions could improve both survival and quality of life of cancer patients. Hyperspectral imaging (HSI) has emerged as a powerful tool for noninvasive cancer detection and diagnosis, with the advantage of avoiding tissue biopsy and providing diagnostic signatures without the need of a contrast agent in real time. We developed a spectral-spatial classification method to distinguish cancer from normal tissue on hyperspectral images. We acquire hyperspectral reflectance images from 450 to 900 nm with a 2-nm increment from tumor-bearing mice. In our animal experiments, the HSI and classification method achieved a sensitivity of 93.7% and a specificity of 91.3%. The preliminary study demonstrated that HSI has the potential to be applied in vivo for noninvasive detection of tumors.
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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.