ArticleProceedings of SPIE--the International Society for Optical Engineering2019
Surgical Aid Visualization System for Glioblastoma Tumor Identification based on Deep Learning and
Article in Proceedings of SPIE--the International Society for Optical Engineering, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
17 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Medical hyperspectral imaging: an updated review of technology advancements and biomedical applications.Journal of biomedical optics · 2026Pooled it
- Precise delineation of glioma margins in hyperspectral images using cross-channel spectral feature fusion.Biomedical optics express · 2026Article
- Spectral Analysis of Extrahepatic Bile Ducts During Normothermic Liver Machine Perfusion.Bioengineering (Basel, Switzerland) · 2025Article
- The impact of histology and molecular biology in refining the prognostic value of surgical margins in head and neck oncology - A narrative review.Acta otorhinolaryngologica Italica : organo ufficiale della Societa italiana di otorinolaringologia e chirurgia cervico-facciale · 2025Article
- Hyperspectral imaging in neurosurgery: a review of systems, computational methods, and clinical applications.Journal of biomedical optics · 2025Review
- Optical Methods for Brain Tumor Detection: A Systematic Review.Journal of clinical medicine · 2024Review
- Impact of Pre- and Post-Processing Steps for Supervised Classification of Colorectal Cancer in Hyperspectral Images.Cancers · 2023Article
- Evaluation of Preprocessing Methods on Independent Medical Hyperspectral Databases to Improve Analysis.Sensors (Basel, Switzerland) · 2022Article
- Hyperspectral Imaging during Normothermic Machine Perfusion-A Functional Classification of Ex Vivo Kidneys Based on Convolutional Neural Networks.Biomedicines · 2022Article
- Intraoperative tissue classification methods in orthopedic and neurological surgeries: A systematic review.Frontiers in surgery · 2022Review
- Review on the Application of Hyperspectral Imaging Technology of the Exposed Cortex in Cerebral Surgery.Frontiers in bioengineering and biotechnology · 2022Review
- VNIR-NIR hyperspectral imaging fusion targeting intraoperative brain cancer detection.Scientific reports · 2021Article
- Article
- Comprehensive review of surgical microscopes: technology development and medical applications.Journal of biomedical optics · 2021Review
- Article
- Most Relevant Spectral Bands Identification for Brain Cancer Detection Using Hyperspectral Imaging.Sensors (Basel, Switzerland) · 2019Article
- In-Vivo and Ex-Vivo Tissue Analysis through Hyperspectral Imaging Techniques: Revealing the Invisible Features of Cancer.Cancers · 2019Review
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
Brain cancer surgery has the goal of performing an accurate resection of the tumor and preserving as much as possible the quality of life of the patient. There is a clinical need to develop non-invasive techniques that can provide reliable assistance for tumor resection in real-time during surgical procedures. Hyperspectral imaging (HSI) arises as a new, noninvasive and non-ionizing technique that can assist neurosurgeons during this difficult task. In this paper, we explore the use of deep learning (DL) techniques for processing hyperspectral (HS) images of
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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.