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Author Notes:

Corresponding author: Baowei Fei, bfei@emory.edu; Web: http://feilab.org.

Subjects:

Research Funding:

This research is supported in part by NIH grants R21CA176684, R01CA156775 and P50CA128301, Georgia Cancer Coalition Distinguished Clinicians and Scientists Award, and the Center for Systems Imaging (CSI) of Emory University School of Medicine.

Keywords:

  • Science & Technology
  • Physical Sciences
  • Life Sciences & Biomedicine
  • Optics
  • Radiology, Nuclear Medicine & Medical Imaging
  • Hyperspectral imaging
  • intraoperative tumor detection
  • wavelength optimization
  • mutual information
  • glare removal
  • active contour
  • support vector machine

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

Tools:

Proceedings Title:

Proceedings of SPIE

Conference Name:

Conference on Medical Imaging - Image-Guided Procedures, Robotic Interventions, and Modeling

Publisher:

Conference Place:

Orlando, FL

Volume/Issue:

Volume 9415

Publication Date:

Type of Work:

Conference | Post-print: After Peer Review

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.

Copyright information:

© 2015 SPIE.

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