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This paper presents a novel and effective method of shape analysis and recognition based on skeleton and morphological structure. A series of preprocessing algorithms, smooth following and liberalization are introduced, and series of morphological structural points of image contour are extracted and merged. A series of basic shapes and a main shape of object image are described and segmented based...
Cervical cancer is the second most common malignancy among women worldwide, if it is detected in early stage, cure rate is relatively high. Computer aided abnormality detection for cervical smear is developed to assist medical experts to handle the microscopy images, examine cell abnormalities and diagnose dyskaryosis. The microscopy images of cells in cervix uteri are stained by the tumor marker...
Cervical cancer is the second most common cancer among women. At the same time, cervical cancer could be largely preventable and curable with regular Pap tests. This test can find nuclei changes in the cervix. Accurate nuclei detection is extremely critical as it is the previous step of analysing nuclei changes and diagnosis afterwards. In recent years, automatic nuclei segmentation has increased...
A fully automated approach is presented to extract brain areas efficiently from FDG-PET head scans. A threshold value is automatically calculated from the histogram graph of the brain images, followed by region growing and morphological operations, to segment brain areas from these images. Next, the midsagittal lines on axial slices are detected to separate the brain into two hemispheres. The proposed...
This paper introduces an interactive and intelligent approach for accurate brain segmentation. A high resolution 3-Tesla magnetic resonance (MR) dataset was tested by state of the art automated algorithms as well as segmented by making use of the proposed interactive tools. The results show that the automated algorithms gave an incomplete or anatomically incorrect brain surface. About 4% false positive...
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