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Anatomical sketch understanding

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dc.contributor.advisor Professor Peter Haddawy (Chairman) en_US
dc.contributor.advisor Dr. Matthew Dailey (Member) en_US
dc.contributor.advisor Dr. Xiaoyong Chen (Member) en_US
dc.contributor.author Ploen Kaewruen en_US
dc.date.accessioned 2015-01-12T10:45:20Z
dc.date.available 2015-01-12T10:45:20Z
dc.date.issued 2005 en_US
dc.identifier.other AIT Thesis no.IM-05-03 en_US
dc.identifier.uri http://www.cs.ait.ac.th/xmlui/handle/123456789/569
dc.description 88 p. en_US
dc.description.abstract Anatomical sketching is widely used in medicine. Physicians often draw sketches in patient records to describe pathology. Medical students frequently use sketches in learning anatomy and communicating in group problem solving. If a computer has the ability to recognize such sketches, it would greatly benefit many medical applications such as automated patient records and education software in medicine. In this thesis, we attempt to develop a system that is capable of recognizing anatomical sketches. We present a method for recognizing sketches that consists of two processes. The first process is an algorithm used for comparing the similarity between a sketch and pre-defined set of templates. The second process focuses on the template selection using the principle of classification. The accuracy of the proposed method is evaluated over a number of sketches drawn by medical students. To measure the effectiveness of the approach, the accuracies of the recognition between the system and human experts are compared. Finally, a prototype system is developed to demonstrate the potential use of anatomical sketch recognition in practice. en_US
dc.description.sponsorship Royal Thai Government Fellowship en_US
dc.language.iso en en_US
dc.publisher Asian Institute of Technology en_US
dc.relation.ispartofseries AIT Publications; en_US
dc.subject Anatomical en_US
dc.subject Sketching en_US
dc.title Anatomical sketch understanding en_US
dc.type Thesis en_US


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