ReviewCancers2019
In-Vivo and Ex-Vivo Tissue Analysis through Hyperspectral Imaging Techniques: Revealing the Invisible Features of Cancer.
Review in Cancers, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07036783 (Multimodal Data Collection for the Development and Validation of the STRATUM Tool to Assist Surgery in Patients Affected by Brain Tumours), which is not on this map. Cited by 97 papers, 3 of them syntheses that pooled 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.
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.
Multimodal Data Collection for the Development and Validation of the STRATUM Tool to Assist Surgery in Patients Affected by Brain Tumours: Observational Study
Who cites it
97 citing papers in PubMed, 3 syntheses or guidelines pooled it, 231 citations in OpenAlex.
- Medical hyperspectral imaging: an updated review of technology advancements and biomedical applications.Journal of biomedical optics · 2026Pooled it
- Hyperspectral imaging in oral oncology: a scoping review.Frontiers in oral health · 2026Pooled it
- Recent Advances in Counterfeit Art, Document, Photo, Hologram, and Currency Detection Using Hyperspectral Imaging.Sensors (Basel, Switzerland) · 2022Pooled it
- Deep Learning-Assisted Accuracy Improvement in Bladder Cancer Staging of Spectrum-Aided Visual Enhanced Cystoscopy Images.Biosensors · 2026Article
- Xeno-learning: knowledge transfer across species in deep learning-based spectral image analysis.Nature biomedical engineering · 2026Article
- Evaluation of the Usefulness of Machine Learning and Artificial Intelligence on Hyperspectral Images in the Diagnosis of Myelodysplastic Syndrome.Journal of biophotonics · 2026Article
- In-vivo detection of cervical cancer lesions using hyperspectral colposcopy.Scientific reports · 2026Article
- Artificial intelligence in respiratory medicine: From diagnosis to treatment and future directions.Chinese medical journal pulmonary and critical care medicine · 2026Review
- High-to-Low Spectral Mapping for Cross-System Feature Adaptation in Medical Hyperspectral Imaging.Bioengineering (Basel, Switzerland) · 2026Article
- Neural illumination calibration for surgical workflow-optimized spectral imaging.International journal of computer assisted radiology and surgery · 2026Article
- Gene Expression Alterations Associated With Resveratrol-Induced Antiproliferative Effects and S-Phase Cell Cycle Arrest in Osteosarcoma Cancer Cells.Journal of cellular and molecular medicine · 2026Article
- Wide-field and non-invasive imaging of brain tumours with scattered light techniques.Biomedical optics express · 2026Article
- Article
- Assisting species differentiation and taxonomic classification by hyperspectral imaging: an example from the parasitic plant realm.Plant methods · 2026Article
- Computed tomography image analysis of cobalt oxide nanoparticles-induced cytopathic effect on Hep-G2 cell lines.RSC advances · 2025Article
- Laparoscopic hyperspectral imaging for in vivo detection of the vagal nerve in upper gastrointestinal surgery.Surgical endoscopy · 2025Article
- Enhancing Oral Health Diagnostics With Hyperspectral Imaging and Computer Vision: Clinical Dataset Study.JMIR medical informatics · 2025Article
- Ocular changes as potential biomarkers for early diagnosis of Alzheimer's disease.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025Review
- Article
- Multi-channel volume density neural radiance field for hyperspectral imaging.Scientific reports · 2025Article
37 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 3 institutions in 2 countries.
Funding
Abstract
In contrast to conventional optical imaging modalities, hyperspectral imaging (HSI) is able to capture much more information from a certain scene, both within and beyond the visual spectral range (from 400 to 700 nm). This imaging modality is based on the principle that each material provides different responses to light reflection, absorption, and scattering across the electromagnetic spectrum. Due to these properties, it is possible to differentiate and identify the different materials/substances presented in a certain scene by their spectral signature. Over the last two decades, HSI has demonstrated potential to become a powerful tool to study and identify several diseases in the medical field, being a non-contact, non-ionizing, and a label-free imaging modality. In this review, the use of HSI as an imaging tool for the analysis and detection of cancer is presented. The basic concepts related to this technology are detailed. The most relevant, state-of-the-art studies that can be found in the literature using HSI for cancer analysis are presented and summarized, both in-vivo and ex-vivo. Lastly, we discuss the current limitations of this technology in the field of cancer detection, together with some insights into possible future steps in the improvement of this technology.
Indexed as
Identifiers
What OpenQuestion holds
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.