a Microscopic Telepathology System for Multiresolution Computer-Aided Diagnostics
.
A Microscopic Telepathology System for Multiresolution Computer-Aided Diagnostics.
Journal of Multimedia, 1(7), 2006
Online Version
A pdf version is available for download.
Abstract
The aim of the presented system is simplification and speedup of the daily pathological examination routine. The system combines telepathology with computer-aided diagnostics algorithms. To the best of our knowledge, this is the first approach proposing such a comprehensive method. Our system is designed to accumulate knowledge through a learning process during diagnostics. Our system targets image acquisition and interpretation stages. The image acquisition subsystem solves various problems related to microscopical slide digitization such as biomedical image registration, data representation, and processing. The interpretation subsystem is based on Gabor filter texture features as well as on color features. A support vector machine classifier together with a feature selection is used for computer-aided diagnostics. The system design allows easy adaptation to a wide range of microscopical pathology examinations. The system is easy deployed and scaled. It has a low support cost and can aggregate a wide range of existing hardware. The experimental validation of the system is based on a database of more than thousand samples. During the experimental evaluation, the system exhibited successful interaction with a pathologist.
Keywords
Co-authors
Bibtex Entry
@article{BegelmanPR06a,
title = {A Microscopic Telepathology System for Multiresolution Computer-Aided Diagnostics},
author = {Grigory Begelman and Michael Pechuk and Ehud Rivlin},
year = {2006},
month = {November-December},
journal = {Journal of Multimedia},
volume = {1},
number = {7},
keywords = {Computer-aided diagnostics; microscopical telepatology, multiresolution analysis},
abstract = {The aim of the presented system is simplification and speedup of the daily pathological examination routine. The system combines telepathology with computer-aided diagnostics algorithms. To the best of our knowledge, this is the first approach proposing such a comprehensive method. Our system is designed to accumulate knowledge through a learning process during diagnostics. Our system targets image acquisition and interpretation stages. The image acquisition subsystem solves various problems related to microscopical slide digitization such as biomedical image registration, data representation, and processing. The interpretation subsystem is based on Gabor filter texture features as well as on color features. A support vector machine classifier together with a feature selection is used for computer-aided diagnostics. The system design allows easy adaptation to a wide range of microscopical pathology examinations. The system is easy deployed and scaled. It has a low support cost and can aggregate a wide range of existing hardware. The experimental validation of the system is based on a database of more than thousand samples. During the experimental evaluation, the system exhibited successful interaction with a pathologist.}
}