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Optimizing Active Contours for Ultrasound Image Analysis of Cardiac Structures

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This work by Silviu Minut explores the application of active contours, or snakes, to delineate regions in noisy and broken ultrasound images, specifically focusing on cardiac structures like the left ventricle. By mathematically defining factors such as smoothness and energy constraints, the model uses optimization to find the optimal perimeter of the target region. This technique is critical for analyzing heart dynamics, such as changes in chamber volume and ejection fraction, which are vital for understanding cardiac function.

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Optimizing Active Contours for Ultrasound Image Analysis of Cardiac Structures

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Presentation Transcript

    1. Interpolation Snakes Work by Silviu Minut

    2. Ultrasound image has noisy and broken boundaries

    3. Snakes, or active contours Seek perimeter of region Perimeter is constrained by factors Smoothness or bending energy Fit to image gradient Fit to fixed points in image Define all factors mathematically and use optimization to find best perimeter Variational search needs starting point.

    4. Classical snake mathematics: Kass et al 1987

    5. Snake models settling down on simulated region

    6. Ultrasound image has noisy and broken boundaries

    7. Analysis of the left ventricle of the heart is critical Change in chamber volume over the heart cycle is critical Ejection fraction is computed over the heart cycle What fraction of blood volume gets squeezed up the aorta compared to largest volume of the ventricle?

    8. Snake seeks optimal fit to data + smoothness + eveness

    9. Can also train a distribution on the parameters of the snake

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