Tissue classification for laparoscopic image understanding based on multispectral texture analysis

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Title: Tissue classification for laparoscopic image understanding based on multispectral texture analysis
Authors: Zhang, Y
Wirkert, SJ
Iszatt, J
Kenngott, H
Wagner, M
Mayer, B
Stock, C
Clancy, NT
Elson, DS
Maier-Hein, L
Item Type: Conference Paper
Abstract: Intra-operative tissue classification is one of the prerequisites for providing context-aware visualization in computer-assisted minimally invasive surgeries. As many anatomical structures are difficult to differentiate in conventional RGB medical images, we propose a classification method based on multispectral image patches. In a comprehensive ex vivo study we show (1) that multispectral imaging data is superior to RGB data for organ tissue classification when used in conjunction with widely applied feature descriptors and (2) that combining the tissue texture with the reflectance spectrum improves the classification performance. Multispectral tissue analysis could thus evolve as a key enabling technique in computer-assisted laparoscopy.
Editors: Webster, RJ
Yaniv, ZR
Issue Date: 18-Mar-2016
Date of Acceptance: 1-Jan-2016
URI: http://hdl.handle.net/10044/1/41490
DOI: https://dx.doi.org/10.1117/12.2216090
ISSN: 1996-756X
Publisher: Society of Photo-optical Instrumentation Engineers (SPIE)
Journal / Book Title: Proceedings of SPIE
Volume: 9786
Copyright Statement: Copyright 2016 Society of Photo Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.
Sponsor/Funder: Commission of the European Communities
Funder's Grant Number: 242991
Conference Name: Conference on SPIE Image-Guided Procedures, Robotic Interventions, and Modeling
Keywords: Science & Technology
Physical Sciences
Life Sciences & Biomedicine
Radiology, Nuclear Medicine & Medical Imaging
tissue classification
multispectral laparoscopy
multispectral texture analysis
Publication Status: Published
Start Date: 2016-02-28
Finish Date: 2016-03-01
Conference Place: San Diego, California, USA
Appears in Collections:Division of Surgery
Faculty of Medicine

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