Evidence map›Paper›PMID 26523083›Full record

ArticleProceedings of SPIE--the International Society for Optical Engineering2015

Quantitative Wavelength Analysis and Image Classification for Intraoperative Cancer Diagnosis with Hyperspectral Imaging.

Guolan Lu, Xulei Qin, Dongsheng Wang, Zhuo Georgia Chen, Baowei Fei

Open access · greenAbstract read
In one paragraph

Article in Proceedings of SPIE--the International Society for Optical Engineering, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 3 pooled it
2.2field-weighted citation impact, top 14% of its field
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

19 citing papers in PubMed, 3 syntheses or guidelines pooled it, 24 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Article
  5. A hyperspectral surgical microscope with super-resolution reconstruction for intraoperative image guidance.Proceedings of SPIE--the International Society for Optical Engineering · 2024
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  13. Tumor Margin Classification of Head and Neck Cancer Using Hyperspectral Imaging and Convolutional Neural Networks.Proceedings of SPIE--the International Society for Optical Engineering · 2018
    Article
  14. Article
  15. Article
  16. Article
  17. Superpixel-based spectral classification for the detection of head and neck cancer with hyperspectral imaging.Proceedings of SPIE--the International Society for Optical Engineering · 2016
    Article
  18. Hyperspectral Imaging of Neoplastic Progression in a Mouse Model of Oral Carcinogenesis.Proceedings of SPIE--the International Society for Optical Engineering · 2016
    Article
  19. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 3 institutions in 1 country.

Guolan LuThe Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA.
Xulei QinDepartment of Radiology and Imaging Sciences, Emory University, Atlanta, GA.
Dongsheng WangDepartment of Hematology and Medical Oncology, Emory University, Atlanta, GA.
Zhuo Georgia ChenDepartment of Hematology and Medical Oncology, Emory University, Atlanta, GA.
Baowei FeiThe Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA ; Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA ; Department of Mathematics & Computer Science, Emory University, Atlanta, GA ; Winship Cancer Institute of Emory University, Atlanta, GA.
Emory University · USGeorgia Institute of Technology · USThe Wallace H. Coulter Department of Biomedical Engineering · US

Funding

uPAR Targeted in Vivo Molecular Magnetic Resonance Imaging of....P50CA128301 · NCI · EMORY UNIVERSITY · PI SCHUSTER, DAVID MICHAEL · 2008 to 2012
$6.8M
MOLECULAR IMAGING DIRECTED, 3D ULTRASOUND-GUIDED, BIOPSY SYSTEMR01CA156775 · NCI · UNIVERSITY OF TEXAS DALLAS · PI FEI, BAOWEI · 2011 to 2016
$1.7M
Targeted fusion biopsy using anti-[18F]FACBC PET/CT and real-time 3D ultrasound gR21CA176684 · NCI · EMORY UNIVERSITY · PI FEI, BAOWEI, MASTER, VIRAJ · 2013 to 2014
$568k
NCI NIH HHS P50 CA128301NCI NIH HHS R01 CA156775NCI NIH HHS R21 CA176684
6 · The paper itself

Abstract

Complete surgical removal of tumor tissue is essential for postoperative prognosis after surgery. Intraoperative tumor imaging and visualization are an important step in aiding surgeons to evaluate and resect tumor tissue in real time, thus enabling more complete resection of diseased tissue and better conservation of healthy tissue. As an emerging modality, hyperspectral imaging (HSI) holds great potential for comprehensive and objective intraoperative cancer assessment. In this paper, we explored the possibility of intraoperative tumor detection and visualization during surgery using HSI in the wavelength range of 450 nm - 900 nm in an animal experiment. We proposed a new algorithm for glare removal and cancer detection on surgical hyperspectral images, and detected the tumor margins in five mice with an average sensitivity and specificity of 94.4% and 98.3%, respectively. The hyperspectral imaging and quantification method have the potential to provide an innovative tool for image-guided surgery.

Indexed as

active contourglare removalHyperspectral imagingintraoperative tumor detectionmutual informationsupport vector machinewavelength optimization

Identifiers

PMID26523083
PMCPMC4625919
OpenAlexW1977077109

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.