ArticleSensors (Basel, Switzerland)2019
Deep Learning-Based Framework for
Article in Sensors (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 67 papers, 4 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
67 citing papers in PubMed, 4 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
- Deep learning in neurosurgery: a systematic literature review with a structured analysis of applications across subspecialties.Frontiers in neurology · 2025Pooled it
- Survival prediction of glioblastoma patients-are we there yet? A systematic review of prognostic modeling for glioblastoma and its clinical potential.Neurosurgical review · 2021Pooled it
- Precise delineation of glioma margins in hyperspectral images using cross-channel spectral feature fusion.Biomedical optics express · 2026Article
- High-efficacy and affordable hyperspectral pancreatic tissue image analysis using near-infrared spectroscopy.Journal of pathology informatics · 2026Article
- Improving Brain Tumor Detection by Cortical Surface and Vessels Segmentation Through RGB-to-HSI Transfer Learning.Cancers · 2026Article
- Classification of esophageal cancer by using hyperspectral data.International journal of computer assisted radiology and surgery · 2026Article
- Assisting species differentiation and taxonomic classification by hyperspectral imaging: an example from the parasitic plant realm.Plant methods · 2026Article
- Exploring the role of preprocessing combinations in hyperspectral imaging for deep learning colorectal cancer detection.Scientific reports · 2025Article
- Artificial Intelligence in the Diagnosis and Treatment of Brain Gliomas.Biomedicines · 2025Review
- Artificial Intelligence in Glioblastoma-Transforming Diagnosis and Treatment.Chinese neurosurgical journal · 2025Review
- Toward real-time margin assessment in breast-conserving surgery with hyperspectral imaging.Scientific reports · 2025Article
- Hyperspectral imaging in neurosurgery: a review of systems, computational methods, and clinical applications.Journal of biomedical optics · 2025Review
- Advancements in real-time oncology diagnosis: harnessing AI and image fusion techniques.Frontiers in oncology · 2025Review
- The roles of patient-derived xenograft models and artificial intelligence toward precision medicine.MedComm · 2024Review
- Spectral analysis comparison of pushbroom and snapshot hyperspectral cameras forJournal of biomedical optics · 2024Article
- Technological Frontiers in Brain Cancer: A Systematic Review and Meta-Analysis of Hyperspectral Imaging in Computer-Aided Diagnosis Systems.Diagnostics (Basel, Switzerland) · 2024Review
- Spectral library and method for sparse unmixing of hyperspectral images in fluorescence guided resection of brain tumors.Biomedical optics express · 2024Article
- Optical Methods for Brain Tumor Detection: A Systematic Review.Journal of clinical medicine · 2024Review
7 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
17 authors.
Funding
Abstract
The main goal of brain cancer surgery is to perform an accurate resection of the tumor, preserving as much normal brain tissue as possible for the patient. The development of a non-contact and label-free method to provide reliable support for tumor resection in real-time during neurosurgical procedures is a current clinical need. Hyperspectral imaging is a non-contact, non-ionizing, and label-free imaging modality that can assist surgeons during this challenging task without using any contrast agent. In this work, we present a deep learning-based framework for processing hyperspectral 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.