Biomedical subjects

Christopher Bowd

Publications and source records attributed to Christopher Bowd.

40 records · Page 3Linked to original sources

PubMed2002

Imaging of the optic disc and retinal nerve fiber layer: the effects of age, optic disc area, refractive error, and gender.

We cross-sectionally examined the relationship between age, optic disc area, refraction, and gender and optic disc topography and retinal nerve fiber layer (RNFL) measurements, using optical imaging techniques. One eye from each of 155 Caucasian subjects (age range 23.0-80.8 y) without ocular pathology was included. Measurements were obtained by using the Heidelberg Retina Tomography (HRT), the GDx Nerve Fiber Analyzer, and the Optical Coherence Tomograph (OCT). The effects of age were small (R2 < 17%) and were limited to specific HRT, GDx, and OCT parameters. Disc area was significantly associated with most HRT parameters and isolated GDx and OCT parameters. Refraction and gender were not significantly associated with any optic disc or RNFL parameters. Although effects of age on the optic disc and RNFL are small, they should be considered in monitoring ocular disease. Optic disc area should be considered when cross-sectionally evaluating disc topography and, to a lesser extent, RNFL thickness.

Adult↗

PubMed2002

Comparing machine learning classifiers for diagnosing glaucoma from standard automated perimetry.

PURPOSE: To determine which machine learning classifier learns best to interpret standard automated perimetry (SAP) and to compare the best of the machine classifiers with the global indices of STATPAC 2 and with experts in glaucoma. METHODS: Multilayer perceptrons (MLP), support vector machines (SVM), mixture of Gaussian (MoG), and mixture of generalized Gaussian (MGG) classifiers were trained and tested by cross validation on the numerical plot of absolute sensitivity plus age of 189 normal eyes and 156 glaucomatous eyes, designated as such by the appearance of the optic nerve. The authors compared performance of these classifiers with the global indices of STATPAC, using the area under the ROC curve. Two human experts were judged against the machine classifiers and the global indices by plotting their sensitivity-specificity pairs. RESULTS: MoG had the greatest area under the ROC curve of the machine classifiers. Pattern SD (PSD) and corrected PSD (CPSD) had the largest areas under the curve of the global indices. MoG had significantly greater ROC area than PSD and CPSD. Human experts were not better at classifying visual fields than the machine classifiers or the global indices. CONCLUSIONS: MoG, using the entire visual field and age for input, interpreted SAP better than the global indices of STATPAC. Machine classifiers may augment the global indices of STATPAC.

Diagnosis, Computer-Assisted↗

PubMed2002

Comparing neural networks and linear discriminant functions for glaucoma detection using confocal scanning laser ophthalmoscopy of the optic disc.

PURPOSE: To determine whether neural network techniques can improve differentiation between glaucomatous and nonglaucomatous eyes, using the optic disc topography parameters of the Heidelberg Retina Tomograph (HRT; Heidelberg Engineering, Heidelberg, Germany). METHODS: With the HRT, one eye was imaged from each of 108 patients with glaucoma (defined as having repeatable visual field defects with standard automated perimetry) and 189 subjects without glaucoma (no visual field defects with healthy-appearing optic disc and retinal nerve fiber layer on clinical examination) and the optic nerve topography was defined by 17 global and 66 regional HRT parameters. With all the HRT parameters used as input, receiver operating characteristic (ROC) curves were generated for the classification of eyes, by three neural network techniques: linear and Gaussian support vector machines (SVM linear and SVM Gaussian, respectively) and a multilayer perceptron (MLP), as well as four previously proposed linear discriminant functions (LDFs) and one LDF developed on the current data with all HRT parameters used as input. RESULTS: The areas under the ROC curves for SVM linear and SVM Gaussian were 0.938 and 0.945, respectively; for MLP, 0.941; for the current LDF, 0.906; and for the best previously proposed LDF, 0.890. With the use of forward selection and backward elimination optimization techniques, the areas under the ROC curves for SVM Gaussian and the current LDF were increased to approximately 0.96. CONCLUSIONS: Trained neural networks, with global and regional HRT parameters used as input, improve on previously proposed HRT parameter-based LDFs for discriminating between glaucomatous and nonglaucomatous eyes. The performance of both neural networks and LDFs can be improved with optimization of the features in the input. Neural network analyses show promise for increasing diagnostic accuracy of tests for glaucoma.

Discriminant Analysis↗

PubMed2002

Assessment of the retinal nerve fiber layer of the normal and glaucomatous monkey with scanning laser polarimetry.

PURPOSE: To describe and test a method for assessment of the monkey retinal nerve fiber layer (RNFL) with scanning laser polarimetry. METHODS: A scanning laser polarimeter was modified to accommodate a variable corneal polarization compensator. Corneal polarization magnitude (CPM) and corneal polarization axis (CPA) of the anterior segment birefringence of normal and glaucomatous cynomolgus monkey eyes were determined from a polarimetry image of the Henle fiber layer. Next, the variable compensator was adjusted to minimize the anterior segment birefringence. RNFL measurements were then obtained. All images were compared with simultaneous optic disc stereoscopic photographs. RESULTS: CPM was small in each of the eyes examined, ranging from 5.7 nm to 9.0 nm. CPA ranged from -62 degrees to 79 degrees. (Nasally upward CPA values were recorded as negative; nasally downward CPA values were recorded as positive.) When eye-specific compensation was used, RNFL retardation profiles mimicked the expected appearance of the RNFL in all eyes. We also observed a substantial decrease in retardation in eyes with experimental glaucoma compared with healthy fellow eyes. CONCLUSIONS: Individualized anterior segment compensation can be achieved in the monkey eye so that the measured birefringence appears to largely reflect the birefringence of the RNFL. Observed differences in retardation between healthy eyes and eyes with experimental glaucoma suggest that scanning laser polarimetry may be useful for detecting and monitoring RNFL loss in experimental primate glaucoma.

Animals↗