Please use this identifier to cite or link to this item:
Title: Intelligent medical instrumentation system for minimally invasive diagnosis procedure for abnormality detection and telediagnosis
Authors: Krishnan Shankar Muthu.
Chan, Kap Luk.
Opas Chutatape.
Chia, Tech Chee.
Keywords: DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Medical electronics
Issue Date: 2006
Abstract: In recent years, minimally invasive endoscopic procedures have been increasingly employed for diagnostic and surgical purposes, thus decreasing the in-hospital stay period and time for recovery of the patient. These procedures are manually performed and analysed by expert endoscopists such as in the gastrointestinal and respiratory cases. Hence these procedures are subjective and require special slulls as well as experience. Development of new algorithms and techniques for computer-based processing of the images and analyzing them to detect abnormalities will enhance the overall efficacy of the minimally invasive procedures. The present project is aimed at the design and development of an efficient endoscopic instrumentation system for abnormality detection and telediagnosis, by incorporation of intelligent modules in image acquisition, image processing, image analysis and decision-malung regarding the presence of abnormalities. This project considers networked configuration of multiple task-sites to facilitate teleconsultation. Testing is carried out on clinical endoscopic images. The results obtained generally support the feasibility of the proposed approach. The experimental results are discussed at length. Refinements are made to the proposed methods for improving the accuracy of abnormality detection. Thus, a computer-based, intelligent, minimally invasive endoscopic has been developed for efficient detection of abnormalities in the gastrointestinal system.
Rights: Nanyang Technological University
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Research Reports (Staff & Graduate Students)

Files in This Item:
File Description SizeFormat 
  Restricted Access
25.54 MBAdobe PDFView/Open

Page view(s) 20

Updated on Nov 26, 2020

Download(s) 20

Updated on Nov 26, 2020

Google ScholarTM


Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.