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Level Set Methods for Cardiac Segmentation in MSCT Images
Published in Ayman El-Baz, Jasjit S. Suri, Level Set Method in Medical Imaging Segmentation, 2019
Ruben Medina, Sebastian Bautista, Villie Morocho, Alexandra La Cruz
where v is the average of pixels inside the contour C where ϕ≥0 and u is the average of pixels outside the contour C where ϕ<0. In this active contour model, the previous energy function is minimized and a regularization term is included. The evolution of the contour is given by Eq. 7.12.
Image Segmentation
Published in Yu-Jin Zhang, A Selection of Image Analysis Techniques, 2023
The active contour model approximates the contour of the object in the image by gradually changing the shape of the closed curve. In this process, the various parts of the object contour are often represented by straight-line segments. The active contour model is also called the snake model, because in the process of approximating the object contour, the closed curve continuously changes its shape like a snake crawling. In practice, the active contour model is often used to detect the actual contour when an approximate initial contour of the object contour in the image is given.
Detection of Calcification from Abdominal Aortic Aneurysm
Published in Ayman El-Baz, Jasjit S. Suri, Cardiovascular Imaging and Image Analysis, 2018
Safa Salahat, Ahmed Soliman, Harish Bhaskar, Tim McGloughlin, Ayman El-Baz, Naoufel Werghi
In [22] Disseldorp et al. performed 3D segmentation of the aorta from ultrasound and compared it to CT. In order to ensure that the whole AAA volume is acquired, additional proximal and distal volumes had to be registered with the whole 3D volume, so that the active contour model suggested by Kass et al. [20] would be used next to segment the volume in 3D. The active contour model relies on internal and image derived external forces and user constraints to control the deformation process. CT volume was segmented using Hemodyn.
A fully automatic methodology for MRI brain tumour detection and segmentation
Published in The Imaging Science Journal, 2019
S. Tchoketch Kebir, S. Mekaoui, M. Bouhedda
Image segmentation using active contour technique (process) becomes an important technique in the field of image processing and segmentation, due to the important advantages offered by this technique and its accuracy for determining the closed and formal contours to target objects [34]. Generally, the active contour model is summarized by the evolution of energy function based on the intrinsic properties of the images; this evolution is based on the level set method. To obtain a minimum energy of curve contour S, this energy minimization is driving the contours curve to snake the interesting region ROI. The initial active contour mask S evolves to separate an image into two regions as shown in Figure 6(a). One region is inside S and the other region is outside S. The curve is located at the boundary between objects and background and finally the active contour mask meets the curve as shown in Figure 6(b).
A sonography image processing system for tumour segmentation
Published in Enterprise Information Systems, 2020
Chung-Ming Chen, Shu-Wei Zhang, Chih-Yu Hsu
Active contour model is used to describe how a contour evolutes to find the boundary of Region of Interest (ROI) for image segmentation. Because the deformation of level set function at zero level represents the deformation of active contour (Osher and Fedkiw 2002), the active contour can be represented by a level set function with the zero level . The active contour separates the inside region and the outside region .