Browsing by Author "Cideciyan, Artur V."

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Open Access
Compensation for patient motion in nuclear medicine renal studies by fast correlation image registration
(1993) Georgiou, Michalis F.; Nagel, Joachim H.; Cideciyan, Artur V.; Sfakianakis, George N.
A computer method has been developed to compensate for patient motion which degrades nuclear medicine renal dynamic studies. The method is based on a fast correlation algorithm which accomplishes decoupling of the registration variables translation, rotation and scaling, and converts rotations into cyclic shifts using polar transformations of the images in the Fourier domain. The method has been implemented into a fully automated program which compensates for translational and rotational differences between images acquired while the patient was immobile and images acquired after the occurrence of motion. Preliminary results indicate the usefulness of the program as a clinical tool for salvaging renal scintigraphic studies with patient motion, thus preventing erroneous interpretations or repeat of the examinations.
Open Access
Digital analysis of high resolution fundus images
(1992) Nagel, Joachim H.; Cideciyan, Artur V.
Fundus photography is a common procedure in ophthalmology providing high resolution images of the inside back portion of the eye to diagnose diseases of the retina and the optic nerve, and to record their progress over time. In many instances, objective, quantitative, reproducible and reliable interpretation of fundus images requires their computerized analysis. A comprehensive system for digital analysis of high resolution fundus images has to address virtuallly all engineering aspects of medical image processing: restoration, segmentation, pattern recognition, and registration. Based on the specific application of investigating the tapetal-like reflex, a retinal reflection uniquely present in carriers of X-linked retinitis pigmentosa (XLRP), novel approaches to the various stages of image processing are presented, and applications in other areas of medical diagnostics are outlined.
Open Access
Modeling of high resolution digital retinal imaging
(1991) Cideciyan, Artur V.; Nagel, Joachim H.; Jacobson, Samuel G.
High resolution digital images of the retina can be obtained by photography with a Zeiss fundus camera followed by digitization of the photographic slide with a high resolution scanner. A complete model of this imaging system is developed based on its four components; the eye, the camera, the film and the scanner. The actual and modeled step responses and system noise are compared to validate the model. A simulated retinal reflection is used to demonstrate the extent of information degradation caused by such an imaging system. Preliminary results of linear restoration using a simplified version of the complete model are given. Development of nonlinear restoration incorporating the complete model is in progress.
Open Access
Multi-modality image registration using the Hough transform
(1990) Cideciyan, Artur V.; Nagel, Joachim H.
We present a method for finding relative translation and rotation between images of different modalities, for cases in which external contours can be approximated by ellipses. The Hough transform is used to map the feature space to the parameter space. The feature space consists of the pixel coordinates and gradient direction of all possible edge points, and the parameter space defines all acceptable ellipses. The difference between ellipse parameters, calculated separately for each image, is used to determine the relative translation and rotation. The images are assumed to be corrected for scale. The method is tested on simulated images and on pairs of actual PET/MRI images of the brain.
Open Access
Multi-scale segmentation of retinal images
(1991) Cideciyan, Artur V.; Jacobson, Samuel G.; Nagel, Joachim H.
Tiny bright golden patches can be seen on the dark retinal background of some carriers of X-linked retinitis pigmentosa, an incurable blinding disease. We are interested in analyzing quantitatively these unique "tapetal-like reflex" patches in order to increase our understanding of the cellular mechanisms of the disease. In this paper, we describe the multi-scale thresholding method and its application to the segmentation of the tapetal-like reflex in high resolution digital fundus images. Multi-scale thresholding is a local thresholding method that generates results very similar to that of human intuition. Unlike other local thresholding methods, our method successfuIly ignores small artifacts in dark regions and simultaneously generats high resolution definitions of objects. Other segmentation applications where there are many bright objects on a darker background should profit from the use of multi-scale thresholding.
Open Access
Patient motion compensation for renal scintigraphic studies by a fast correlation image registration method
(1994) Georgiou, Michalis F.; Sfakianakis, George N.; Nagel, Joachim H.; Cideciyan, Artur V.
A computer method has been developed to compensate for patient motion which is a serious problem in real scintigraphic studies. The developed computer method compensates for translational and rotational differences between images acquired while the patient was not moving and images acquired after the occurrence of motion.
Open Access
Registration of high resolution images of the retina
(1992) Cideciyan, Artur V.; Jacobson, Samuel G.; Kemp, Colin M.; Knigthon, Robert W.; Nagel, Joachim H.
A method of image registration is presented for the case when the deformation between two images can be well approximated with a combination of translation, rotation and global scaling. The method achieves very high accuracy by combining a global optimization in the 4-dimensional discrete parameter space with a local optimization in the 4-dimensional continuous parameter space. The 4-dimensional global optimization is accomplished with two 2-dimensional optimizations. The Fourier magnitude is used to decouple translation from rotation and scaling, and a log-polar mapping of the Fourier magnitude is used to convert rotation and scaling into shifts. Optimal rotation and scaling parameters are determined with a cross-correlation in the log-polar domain. After compensation for rotation and scaling differences, cross-correlation in the spatial domain yields the translation parameters. The four registration parameters are further refined with a local optimization using the correlation coefficient as a similarity measure in the 4-dimensional continuous parameter space. Results are shown from simulations and from registration of retinal images. For simulated images with a signal-to-noise ratio of -5 dB, the accuracy of the registration method is estimated to be better than 0.07 degrees, 0.1 %, and 0.3 pixels for rotation, scaling, and translation, respectively. In the case of 512x512 pixel images the computation resource requirements are compatible with high end PCs, i.e., approximately 25 minutes on an Intel 80486/33MHz based IBM/PC compatible.