Abstract/Details

Segmentation automatique d'image pour le suivi des cicatrices suite à une chirurgie de la scoliose

Hurtut, Thomas.   Ecole Polytechnique, Montreal (Canada) ProQuest Dissertations & Theses,  2003. MQ86402.

Abstract (summary)

The goal of this project is to propose to the plastic surgeons a data-processing methodology that analyzes images, making it possible to easily measure some of the criteria used: dimensional and chromatic criteria. Such a tool also makes it possible to proceed to the constitution of data banks on scars and their evolutions. Such quantitative studies would allow to compare methods and clinical tools brought into play in the plastic surgery. For example, it would become possible to compare the various manners of closing a scar, the various types of closing wire etc. These stakes have direct repercussions at the industrial level. The problem of the study of the scars in image processing is new, and remains as still an open research field.

This methodology is based on the INSPECK acquisition system—INSPECK Inc, Montreal—which is a active vision system composed of optical digitizers. (Abstract shortened by UMI.)

Indexing (details)


Subject
Computer science
Classification
0984: Computer science
Identifier / keyword
Applied sciences; French text
Title
Segmentation automatique d'image pour le suivi des cicatrices suite à une chirurgie de la scoliose
Alternate title
Automated Image Segmentation for Scoliosis Surgery Scar Tracking
Author
Hurtut, Thomas
Number of pages
148
Publication year
2003
Degree date
2003
School code
1105
Source
MAI 42/04M, Masters Abstracts International
ISBN
978-0-612-86402-3
University/institution
Ecole Polytechnique, Montreal (Canada)
University location
Canada -- Quebec, CA
Degree
M.Sc.A.
Source type
Dissertation or Thesis
Language
French
Document type
Dissertation/Thesis
Dissertation/thesis number
MQ86402
ProQuest document ID
305254201
Copyright
Database copyright ProQuest LLC; ProQuest does not claim copyright in the individual underlying works.
Document URL
https://www.proquest.com/docview/305254201