segmentation and three‑dimensional (3d) visualization of teeth in dental computerized tomography (ct) images are of dentists’ requirements for both abnormalities diagnosis and the treatments such as dental implant and orthodontic planning. on the other hand, dental ct image segmentation is a difficult process because of the specific characteristics of the tooth’s structure. this paper presents ...

‎this paper presents an application of partial differential equations(pdes) for the segmentation of abdominal and thoracic aortic in cta datasets. an important challenge in reliably detecting aortic is the need to overcome problems associated with intensity inhomogeneities. level sets are part of an important class of methods that utilize partial differential equations (pdes) and have been exte...

breast lesion segmentation in mr images is one of the most important parts of clinical diagnostic tools. pixel classification methods have been frequently used in image segmentation with two supervised and unsupervised approaches up to now. supervised segmentation methods lead to high accuracy, but they need a large amount of labeled data, which is hard, expensive, and slow to be obtained. on t...

This paper presents a parallel implementation of color image segmentation algorithm using multiresolution technique. The idea is to achieve the complete and significant objects in the image using contourlet transform based image segmentation and to explore current multi-core architectures present in commercial processors in order to speed up the segmentation process for large size images. The a...

Retinal image processing is a standard medical repetition and offers number of profitable products for physicians. In the field of retinal image processing retinal vessel segmentation is the crucial task for detection of cardiovascular diseases in advance. The recognition of erroneous blood vessel may cause in incorrect clinical diagnosis. Various processing steps are required for the extractio...

Image segmentation is one of the most common steps in digital image processing. The area many image segmentation algorithms (e.g., thresholding, edge detection, and region growing) employed for classifying a digital image into different segments. In this connection, finding a suitable algorithm for medical image segmentation is a challenging task due to mainly the noise, low contrast, and steep...