Sun-Worl Kim

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In this paper, we present an automatic segmentation method for medical image based on the statistical technique. Here we use the morphological operations to determine automatically the number of clusters or objects composing a given image without any prior knowledge and adopt the Gaussian mixture model to mode an image statistically. Next, the deterministic(More)
This paper presents a new hybrid speed function needed to perform image segmentation within the level-set framework. This speed function provides a general form that incorporates the alignment term as a part of the driving force for the proper edge direction of an active contour by using the probability term derived from the region partition scheme and, for(More)
In this paper, we present a new segmentation method using the level set framework for medical volume images. The method was implemented using the surface evolution principle based on the geometric deformable model and the level set theory. And, the speed function in the level set approach consists of a hybrid combination of three integral measures derived(More)
In this paper, we propose a new image registration technique using two kinds of information known as object shapes and voxel intensities. The proposed approach consists of two registration steps. First, an initial registration is carried out for two volume images by applying Procrustes analysis theory to the two sets of 3D feature points representing object(More)
The level set approach can be used as powerful tool for volume segmentation of a region-of-interest (ROI), to achieve an accurate estimation of tumor or soft tissue in medical images. A major challenge of such algorithms is required to set the equation parameters, especially in the speed function. In this paper, we introduce a geometric active surface(More)
The problems of segmentation and registration are traditionally approached separately; yet the accuracy of one is of great importance in influencing the accuracy of the other. We propose a new method, using shape information and a statistical model, to address the problem of multimodality medical image registration. Using the approach presented in this(More)