Digital geometry image analysis for medical diagnosis

This paper describes a new medical image analysis technique for polygon mesh surfaces of human faces for a medical diagnosis application. The goal is to explore the natural patterns and 3D facial features to provide diagnostic information for Fetal Alcohol Syndrome (FAS). Our approach is based on a digital geometry analysis framework that applies pattern recognition techniques to digital geometry (polygon mesh) data from 3D laser scanners and other sources. Novel 3D geometric features are extracted and analyzed to determine the most discriminatory features that best represent FAS characteristics. As part of the NIH Consortium for FASD, the techniques developed here are being applied and tested on real patient datasets collected by the NIH Consortium both within and outside the US. Categories and Subject Descriptors I.5.2 [Pattern Recognition]: Design Methodology – Feature evaluation and selection. I.3.5 [Computer Graphics]: Computational Geometry and Object Modeling – Geometric al...

• Type: Conference
• Year: 2006
• Where: SAC
• Authors: Jiandong Fang, Shiaofen Fang, Jeffrey Huang, Mihran Tuceryan
• Keywords: Applied Computing, Digital Geometry, Fetal Alcohol Syndrome, Pattern Recognition, SAC 2006