This paper presents a fully automatic segmentation method of liver CT scans using fuzzy c-mean clustering and level set. First, the contrast of original image is enhanced to make boundaries clearer; second, a spatial fuzzy c-mean clustering combining with anatomical prior knowledge is employed to extract liver region automatically; thirdly, a distance regularized level set is used for refinemen...

In many applications, denoising is necessary since point-sampled models obtained by laser scanners with insufficient precision. An algorithm for point-sampled surface is presented, which combines fuzzy c-means clustering with mean shift filtering algorithm. By using fuzzy c-means clustering, the largescale noise is deleted and a part of small-scale noise also is smooth. The cluster centers are ...

Accurate segmentation is an important and challenging task in any computer vision system. It also plays a vital role in computerized analysis of skin lesion images. This paper presents a new segmentation method that combines the advantages of fuzzy C mean algorithm, thresholding and level set method. 3-class Fuzzy C mean thresholding is applied to initialize level set automatically and also for...

Artificial recharge can be an effective method to raise the groundwater table and to resolve the groundwater crisis in Sefid dasht plain. The most important step to successful accomplishment of artificial recharge is locating suitable areas for artificial recharge. Hence this research carried out with purpose of determining suitable areas for artificial recharge in Sefid dasht plain. Slope, sur...

Artificial recharge can be an effective method to raise the groundwater table and to resolve the groundwater crisis in Sefid dasht plain. The most important step to successful accomplishment of artificial recharge is locating suitable areas for artificial recharge. Hence this research carried out with purpose of determining suitable areas for artificial recharge in Sefid dasht plain. Slope, sur...