Hyperspectral microscopic imaging for the detection of head and neck squamous cell carcinoma on histologic slides

Ling Ma, Ximing Zhou, James V. Little, Amy Y. Chen, Larry L. Myers, Baran D. Sumer, Baowei Fei

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The purpose of this study is to explore the feasibility of using hyperspectral imaging (HSI) for automatic detection of head and neck squamous cell carcinoma (SCC) in histologic images. Histologic slides from 14 patients with SCC of the larynx, hypopharynx, and buccal mucosa were scanned to train and test an Inception-based two-dimensional convolutional neural network (CNN). The average accuracy, sensitivity and specificity of the HSI patch-based CNN classification were 0.80, 0.82 and 0.78, respectively. The hyperspectral microscopic imaging and proposed classification method provide an automatic tool to aid pathologists in detecting SCC on histologic slides.

Original languageEnglish (US)
Title of host publicationMedical Imaging 2021
Subtitle of host publicationDigital Pathology
EditorsJohn E. Tomaszewski, Aaron D. Ward
PublisherSPIE
ISBN (Electronic)9781510640351
DOIs
StatePublished - 2021
EventMedical Imaging 2021: Digital Pathology - Virtual, Online, United States
Duration: Feb 15 2021Feb 19 2021

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume11603
ISSN (Print)1605-7422

Conference

ConferenceMedical Imaging 2021: Digital Pathology
CountryUnited States
CityVirtual, Online
Period2/15/212/19/21

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Biomaterials
  • Atomic and Molecular Physics, and Optics
  • Radiology Nuclear Medicine and imaging

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