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Image retrieval from distributed database is one of the challenging tasks in recent researches. Unlike text retrieval through SQL, MYSQL, etc, image retrieval is not an easy task because of its storage space, color, shape and texture factor. We propose a technique of retrieving images from a distributed database environment by giving a region of an image as an input query. By applying segmentation...
This paper presents a novel, fast and semi-automatic method for accurate cell cluster segmentation and cell counting of digital tissue image samples. In pathological conditions, complex cell clusters are a prominent feature in tissue samples. Segmentation of these clusters is a major challenge for development of an accurate cell counting methodology. We address the issue of cluster segmentation by...
Liver segmentation on computed tomography (CT) slices is a challenging task because the images are often corrupted by noise and sampling artifacts. Recent years fast marching method (FMM) has been introduced into the image segmentation domain and proved to have advantage in blur edge detection. When apply the FMM to the segmentation of liver CT slice, to attain the completely liver shape, an over-segmentation...
In this paper, we propose a new approach that we call the ldquofluid vector flowrdquo (FVF) active contour model to address problems of insufficient capture range and poor convergence for concavities. With the ability to capture a large range and extract concave shapes, FVF demonstrates improvements over techniques like gradient vector flow, boundary vector flow, and magnetostatic active contour on...
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