Using Computers for Assessment of Facial Features and Recognition of Anatomical Variants that Result in Unfavorable Rhinoplasty Outcomes

Rhinoplasty and facial plastic surgery are among the most frequently performed surgical procedures in the world. Although the underlying anatomical features of nose and face are very well known, performing a successful facial surgery requires not only surgical skills but also aesthetical talent from...

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Main Authors: Tarik Ozkul, Murat Haluk Ozkul
Format: Article
Language:English
Published: International Institute of Informatics and Cybernetics 2008-04-01
Series:Journal of Systemics, Cybernetics and Informatics
Subjects:
Online Access:http://www.iiisci.org/Journal/CV$/sci/pdfs/T052HMB.pdf
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spelling doaj-59088b1718734e009964eb13f5a1311d2020-11-24T20:53:32ZengInternational Institute of Informatics and CyberneticsJournal of Systemics, Cybernetics and Informatics1690-45242008-04-01622835Using Computers for Assessment of Facial Features and Recognition of Anatomical Variants that Result in Unfavorable Rhinoplasty OutcomesTarik Ozkul0Murat Haluk Ozkul1 American University of Sharjah Vakif Guraba Hospital Rhinoplasty and facial plastic surgery are among the most frequently performed surgical procedures in the world. Although the underlying anatomical features of nose and face are very well known, performing a successful facial surgery requires not only surgical skills but also aesthetical talent from surgeon. Sculpting facial features surgically in correct proportions to end up with an aesthetically pleasing result is highly difficult. To further complicate the matter, some patients may have some anatomical features which affect rhinoplasty operation outcome negatively. If goes undetected, these anatomical variants jeopardize the surgery causing unexpected rhinoplasty outcomes. In this study, a model is developed with the aid of artificial intelligence tools, which analyses facial features of the patient from photograph, and generates an index of "appropriateness" of the facial features and an index of existence of anatomical variants that effect rhinoplasty negatively. The software tool developed is intended to detect the variants and warn the surgeon before the surgery. Another purpose of the tool is to generate an objective score to assess the outcome of the surgery.http://www.iiisci.org/Journal/CV$/sci/pdfs/T052HMB.pdf Fuzzy modellingHarmony indexLow dorsumRhinoplastyFacial harmonyLow radixFacial proportionsFuzzy Logic
collection DOAJ
language English
format Article
sources DOAJ
author Tarik Ozkul
Murat Haluk Ozkul
spellingShingle Tarik Ozkul
Murat Haluk Ozkul
Using Computers for Assessment of Facial Features and Recognition of Anatomical Variants that Result in Unfavorable Rhinoplasty Outcomes
Journal of Systemics, Cybernetics and Informatics
Fuzzy modelling
Harmony index
Low dorsum
Rhinoplasty
Facial harmony
Low radix
Facial proportions
Fuzzy Logic
author_facet Tarik Ozkul
Murat Haluk Ozkul
author_sort Tarik Ozkul
title Using Computers for Assessment of Facial Features and Recognition of Anatomical Variants that Result in Unfavorable Rhinoplasty Outcomes
title_short Using Computers for Assessment of Facial Features and Recognition of Anatomical Variants that Result in Unfavorable Rhinoplasty Outcomes
title_full Using Computers for Assessment of Facial Features and Recognition of Anatomical Variants that Result in Unfavorable Rhinoplasty Outcomes
title_fullStr Using Computers for Assessment of Facial Features and Recognition of Anatomical Variants that Result in Unfavorable Rhinoplasty Outcomes
title_full_unstemmed Using Computers for Assessment of Facial Features and Recognition of Anatomical Variants that Result in Unfavorable Rhinoplasty Outcomes
title_sort using computers for assessment of facial features and recognition of anatomical variants that result in unfavorable rhinoplasty outcomes
publisher International Institute of Informatics and Cybernetics
series Journal of Systemics, Cybernetics and Informatics
issn 1690-4524
publishDate 2008-04-01
description Rhinoplasty and facial plastic surgery are among the most frequently performed surgical procedures in the world. Although the underlying anatomical features of nose and face are very well known, performing a successful facial surgery requires not only surgical skills but also aesthetical talent from surgeon. Sculpting facial features surgically in correct proportions to end up with an aesthetically pleasing result is highly difficult. To further complicate the matter, some patients may have some anatomical features which affect rhinoplasty operation outcome negatively. If goes undetected, these anatomical variants jeopardize the surgery causing unexpected rhinoplasty outcomes. In this study, a model is developed with the aid of artificial intelligence tools, which analyses facial features of the patient from photograph, and generates an index of "appropriateness" of the facial features and an index of existence of anatomical variants that effect rhinoplasty negatively. The software tool developed is intended to detect the variants and warn the surgeon before the surgery. Another purpose of the tool is to generate an objective score to assess the outcome of the surgery.
topic Fuzzy modelling
Harmony index
Low dorsum
Rhinoplasty
Facial harmony
Low radix
Facial proportions
Fuzzy Logic
url http://www.iiisci.org/Journal/CV$/sci/pdfs/T052HMB.pdf
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