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Abstract #57521 Published in IGR 16-2
Detecting abnormality in optic nerve head images using a feature extraction analysis
Zhu H; Poostchi A; Vernon SA; Crabb DPBiomedical optics express 2014; 5: 2215-2230
Imaging and evaluation of the optic nerve head (ONH) plays an essential part in the detection and clinical management of glaucoma. The morphological characteristics of ONHs vary greatly from person to person and this variability means it is difficult to quantify them in a standardized way. We developed and evaluated a feature extraction approach using shift-invariant wavelet packet and kernel principal component analysis to quantify the shape features in ONH images acquired by scanning laser ophthalmoscopy (Heidelberg Retina Tomograph [HRT]). The methods were developed and tested on 1996 eyes from three different clinical centers. A shape abnormality score (SAS) was developed from extracted features using a Gaussian process to identify glaucomatous abnormality. SAS can be used as a diagnostic index to quantify the overall likelihood of ONH abnormality. Maps showing areas of likely abnormality within the ONH were also derived. Diagnostic performance of the technique, as estimated by ROC analysis, was significantly better than the classification tools currently used in the HRT software - the technique offers the additional advantage of working with all images and is fully automated.
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Classification:
2.14 Optic disc (Part of: 2 Anatomical structures in glaucoma)
6.9.1.1 Confocal Scanning Laser Ophthalmoscopy (Part of: 6 Clinical examination methods > 6.9 Computerized image analysis > 6.9.1 Laser scanning)
6.9.5 Other (Part of: 6 Clinical examination methods > 6.9 Computerized image analysis)
