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Opas Chutatape

Publications and source records attributed to Opas Chutatape.

3 recordsLinked to original sources

Auto-adjusted 3-D optic disk viewing from low-resolution stereo fundus image.

Three-dimensional (3-D) visualization of the optic nerve head (optic disk) is very useful for clinical applications. It allows clinicians to measure the disk parameters more accurately and thus make the pathological diagnosis and progression monitoring easier. This paper describes an automatic, precise, 3-D optic nerve head reconstruction method from a pair of stereo images for which efficient steps including sparse-image registration and dense-depth recovery are used. A combination of two registration methods is used to detect the sub-pixel correspondences. The proposed method takes advantages of both the correlation methods which is robust to noise and the feature-based method on its accuracy. The searching range in image registration is auto-adjusted based on the previous iteration result. Only sparse matched points are computed to speed up the processing and the sub-pixel matching is used to overcome the problem of low resolution in the image. This is followed by the piecewise cubic interpolation to obtain the dense disparities and depths. Multiple windowing is applied here by first using the large window to obtain basic disparities followed by the small window and previous basic disparities to measure details. The result is then smoothed and displayed as the final 3-D shape.

Algorithms↗

Automated feature extraction in color retinal images by a model based approach.

Color retinal photography is an important tool to detect the evidence of various eye diseases. Novel methods to extract the main features in color retinal images have been developed in this paper. Principal component analysis is employed to locate optic disk; A modified active shape model is proposed in the shape detection of optic disk; A fundus coordinate system is established to provide a better description of the features in the retinal images; An approach to detect exudates by the combined region growing and edge detection is proposed. The success rates of disk localization, disk boundary detection, and fovea localization are 99%, 94%, and 100%, respectively. The sensitivity and specificity of exudate detection are 100% and 71%, correspondingly. The success of the proposed algorithms can be attributed to the utilization of the model-based methods. The detection and analysis could be applied to automatic mass screening and diagnosis of the retinal diseases.

Algorithms↗

Detection and measurement of retinal vessels in fundus images using amplitude modified second-order Gaussian filter.

In this paper, the fitness of estimating vessel profiles with Gaussian function is evaluated and an amplitude-modified second-order Gaussian filter is proposed for the detection and measurement of vessels. Mathematical analysis is given and supported by a simulation and experiments to demonstrate that the vessel width can be measured in linear relationship with the "spreading factor" of the matched filter when the magnitude coefficient of the filter is suitably assigned. The absolute value of vessel diameter can be determined simply by using a precalibrated line, which is typically required since images are always system dependent. The experiment shows that the inclusion of the width measurement in the detection process can improve the performance of matched filter and result in a significant increase in success rate of detection.

Computer Simulation↗