Active contours based on weighted gradient vector flow and balloon forces for medical image segmentation

Abstract

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Performance Evaluation of Contour Based Segmentation Methods for Ultrasound Images

“…In medical imaging, the segmentation of regions with specific parameters is carried out with the help of active contour models. Because these models develop a contour around the target object and segregate it from the image, the segmented image possesses only the required information of the target object [15]. The level set segmentation methods like Caselles, Chan-Vese, Bernard, Li, and Lankton are applied on arthritis affected finger joint images obtained from the MEDUSA database http://medusa.aei.polsl.pl.…”

Active Contour Based Segmentation Techniques for Medical Image Analysis

“…Because these models develop a contour around the target object and segregates it from the image. The segmented image possesses only the required information of the target object [10].…”

“…Contour is formed for separation of lesions, tissue regions, infected cells, and parasites from the images. 3-D mesh formation is mainly used in the reconstruction of 3-D images from different imaging modalities [10]. 3-D models can also be designed for artificial implants using mesh technique based on the inflation balloon force.…”

Weighted Level Set Evolution Based on Local Edge Features for Medical Image Segmentation

“…To this end, we propose a weighting function to assign different priorities to the area and length terms according to the image features of the adjacent region located inside and outside of C. These features are the average edge intensity, denoted by I, and average difference between the direction of the image's GVF and the normal direction of movement of C, denoted by γ. Note that analyzing the adjacent region located both inside and outside of C, provides an accurate insight of the location of edges, which helps the zero level set to accurately conform to the desired boundary [45]. Our proposed length and area terms then include a weighting factor, ω, that determines their importance in locating the desired boundary according to local edge features.…”

“…Motivated by our previous work [45], we propose a segmentation method that employs an active contour implemented using a variational level set method that weights the level set evolution according to local edge features in order to accurately drive the motion of the zero level set towards the desired boundary. Specifically, our method controls the influence of energy terms in the objective functional with a weighting function that takes into account two local edge features: edge intensities and edge orientations.…”