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检索条件"主题词=Adaptive Exploratory Algorithm"

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A Novel Automated Retinal Image Fusion using adaptive exploratory algorithm and Mutual-Pixel-Count Maximization

A Novel Automated Retinal Image Fusion using Adaptive Explor...

引用

40th Southeastern Symposium on System Theory (SSST 2008)

作者： Hua Cao Nathan Brener Hilary Thompson S. S. Iyengar Zhengmao Ye Department of Computer Science Louisiana State University Baton Rouge USA Electrical Engineering Department Southern University Baton Rouge USA

ISBN: (纸本)9781424418060

A novel automated approach of the multi-modality retinal image registration and fusion has been developed. The new algorithm, which is reliable, robust, and time-efficient, has an automatic adaptation from frame to frame with few tunable threshold parameters. The registration is based on retinal vasculature extraction using Canny Edge Detector, and control point identification at the vessel bifurcations using adaptive exploratory algorithm. Shape similarity criteria are employed to match the control points. MPC maximization based optimization has been developed to adjust the control points at the sub-pixel level. MPC, which is initially introduced by this study into the biomedical image fusion area, is the new measurement criteria for fusion accuracy. A global maxima equivalent result is achieved by calculating MPC local maxima with an efficient computation cost. The comparative study has shown the advantage of the new approach in terms of novelty, efficiency, and accuracy.

关键词： Area-based fusion Feature-based registration Biomedical image registration and fusion adaptive exploratory algorithm Mutual-pixel-count Retinal vasculature extraction

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Automated Control Point Detection, Registration, and Fusion of Fuzzy Retinal Vasculature Images

Automated Control Point Detection, Registration, and Fusion ...

引用

IEEE International Conference on Fuzzy Systems

作者： Cao, Hua Brener, Nathan Thompson, Hilary Iyengar, S. S. Ye, Zhengmao Louisiana State Univ Dept Comp Sci Baton Rouge LA 70802 USA LSU Eye Ctr Dept Ophthalmol New Orleans LA 70112 USA Southern Univ Dept Elect Engn Baton Rouge LA 70813 USA

ISBN: (纸本)9781424418183

Multi-modality biomedical images' feature detection, registration, and fusion are usually scene dependent which requires intensive computational effort. A novel automated approach of the multi-modality retinal image control point detection, registration, and fusion is proposed in this paper. The new algorithm is reliable and time efficient, which implements automatic adaptation from frame to frame with a few tunable thresholds. The reference and input images are from two different modalities, i.e., the angiogram grayscale and fundus true color images. Retinal image's properties determine the fuzzy vessel boundaries and bifurcations. The retinal vasculature is extracted using Canny Edge Detector and the control points are detected at the fuzzy vasculature bifurcations using the adaptive exploratory algorithm. Shape similarity criteria are employed to match the control point pairs. The proposed heuristic optimization algorithm adjusts the control points at the sub-pixel level in order to maximize the objective function Mutual-Pixel-Count (MPC). The iteration stops either when f(MPC) reaches the maximal, or when the maximum allowable loop count is reached. The comparative analysis with other existing approaches has shown the advantages of the new algorithm in terms of novelty, efficiency, and accuracy.

关键词： Control Point Detection Biomedical Imaging Biomedical Image Registration Biomedical Image Fusion Fuzzy Vasculature Boundaries adaptive exploratory algorithm Mutual-Pixel-Count Heuristic Optimization

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Automated registration and fusion of the multi-modality retinal images

Automated registration and fusion of the multi-modality reti...

引用

40th Southeastern Symposium on System Theory

作者： Cao, Hua Brener, Nathan Thompson, Hilary Iyengar, S. S. Ye, Zhengmao Louisiana State Univ Dept Comp Sci Baton Rouge LA 70803 USA Southern Univ Dept Elect Engn Baton Rouge LA 70813 USA

ISBN: (纸本)9781424418060

Biomedical image fusion is generally scene dependent, which requires intensive computational effort. A novel approach of feature-based registration and area-based heuristic optimization fusion of multi-modality retinal images is proposed in this paper. The new algorithm, which is reliable, robust, and time-efficient, has an automatic adaptation from frame to frame with few tunable threshold parameters. The registration approach is based on the retinal vasculature extraction using Canny Edge Detector, and control point identification at the vessel bifurcations using the adaptive exploratory algorithm. The shape similarity criteria are employed to fit the control points. The new fusion approach implements the Mutual-Pixel-Count (MPC) maximization based heuristic optimization procedure, which adjusts the control points at the sub-pixel level. MPC is the new measurement criteria for fusion accuracy being proposed. This study achieved a global maxima equivalent result by calculating MPC local maxima with an efficient computation cost. The new method is a promising step towards useful clinical tools for retinopathy diagnosis, and thus forms a good foundation for further development.

关键词： biomedical image registration and fusion adaptive exploratory algorithm control point detection mutual-pixel-count retinal vasculature extraction heuristic optimization

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A novel automated approach of multi-modality retinal image registration and fusion

A novel automated approach of multi-modality retinal image r...

引用

作者： Cao, Hua Louisiana State University

学位级别：博士

Biomedical image registration and fusion are usually scene dependent, and require intensive computational effort. A novel automated approach of feature-based control point detection and area-based registration and fusion of retinal images has been successfully designed and developed. The new algorithm, which is reliable and time-efficient, has an automatic adaptation from frame to frame with few tunable threshold parameters. The reference and the to-be-registered images are from two different modalities, i. e. angiogram grayscale images and fundus color images. The relative study of retinal images enhances the information on the fundus image by superimposing information contained in the angiogram image. Through the thesis research, two new contributions have been made to the biomedical image registration and fusion area. The first contribution is the automatic control point detection at the global direction change pixels using adaptive exploratory algorithm. Shape similarity criteria are employed to match the control points. The second contribution is the heuristic optimization algorithm that maximizes Mutual-Pixel-Count (MPC) objective function. The initially selected control points are adjusted during the optimization at the sub-pixel level. A global maxima equivalent result is achieved by calculating MPC local maxima with an efficient computation cost. The iteration stops either when MPC reaches the maximum value, or when the maximum allowable loop count is reached. To our knowledge, it is the first time that the MPC concept has been introduced into biomedical image fusion area as the measurement criteria for fusion accuracy. The fusion image is generated based on the current control point coordinates when the iteration stops. The comparative study of the presented automatic registration and fusion scheme against Centerline Control Point Detection algorithm, Genetic algorithm, RMSE objective function, and other existing data fusion approaches has shown the advant

关键词： Biomedical Image Fusion Biomedical Imaging adaptive exploratory algorithm Control Point Detection Biomedical Image Registration Mutual-Pixel-Count Heuristic Optimization algorithm

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Automated Registration and Fusion of the Multi-Modality Retinal Images

Automated Registration and Fusion of the Multi-Modality Reti...

引用

40th Southeastern Symposium on System Theory (SSST 2008)

作者： Hua Cao Nathan Brener Hilary Thompson S. S. Iyengar Zhengmao Ye Department of Computer Science Louisiana State University Baton Rouge LA USA Electrical Engineering Department Southern University Baton Rouge LA USA

ISBN: (纸本)9781424418060

关键词： Biomedical Image Registration and fusion adaptive exploratory algorithm Control Point Detection Mutual-pixel-count Retinal Vasculature Extraction Heuristic Optimization

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