Blood vessel segmentation in narrow band imaging bronchoscopic video

Saptarashmi Bandyopadhyay, Vahid Daneshpajooh, Danish Ahmad, Jennifer Toth, Rebecca Bascom, William E. Higgins

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

Abstract

Lung cancer is the leading cause of cancer fatalities in the world. A recent trend has begun to focus on the idea of using bronchoscopy for early detection of suspect cancerous lesions developing along the airway walls. Because standard white-light bronchoscopy has insufficient sensitivity in locating suspect lesions, researchers are turning to the promising modality referred to as narrow band imaging (NBI). NBI bronchoscopy has the advantage of highlighting the blood vessels contained in the lung mucosa. Since cancer lesions tend to exhibit abnormal vessel growth, NBI bronchoscopy is able to highlight such lesions. Unfortunately, the task of locating lesions and their vessel patterns in an NBI bronchoscopy video stream proves to be tedious for the physician. We present automatic methods for enhancing and segmenting the major blood vessels depicted in NBI bronchoscopic video. Results with ground-Truth data indicate that our methods can achieve superior results to a popular existing vessel-segmentation method. We also consider a preliminary application of deep learning to this task; while this approach gives low sensitivity compared to the other approaches, it achieves higher specificity and accuracy.

Original languageEnglish (US)
Title of host publicationMedical Imaging 2021
Subtitle of host publicationBiomedical Applications in Molecular, Structural, and Functional Imaging
EditorsBarjor S. Gimi, Andrzej Krol
PublisherSPIE
ISBN (Electronic)9781510640290
DOIs
StatePublished - 2021
EventMedical Imaging 2021: Biomedical Applications in Molecular, Structural, and Functional Imaging - Virtual, Online, United States
Duration: Feb 15 2021Feb 19 2021

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume11600
ISSN (Print)1605-7422

Conference

ConferenceMedical Imaging 2021: Biomedical Applications in Molecular, Structural, and Functional Imaging
CountryUnited States
CityVirtual, Online
Period2/15/212/19/21

All Science Journal Classification (ASJC) codes

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

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