Telehealth is the exchange of health information and the provision of health care services through electronic information and\r\ncommunications technology, where participants are separated by geographic, time, social and cultural barriers. The shift of\r\ntelemedicine from desktop platforms to wireless and mobile technologies is likely to have a significant impact on healthcare in\r\nthe future. It is therefore crucial to develop a general information exchange e-medical system to enables its users to perform\r\nonline and offline medical consultations through diagnosis. During the medical diagnosis, image analysis techniques combined\r\nwith doctor�s opinions could be useful for final medical decisions. Quantitative analysis of digital images requires detection and\r\nsegmentation of the borders of the object of interest. In medical images, segmentation has traditionally been done by human\r\nexperts. Even with the aid of image processing software (computer-assisted segmentation tools), manual segmentation of 2D and\r\n3D CT images is tedious, time-consuming, and thus impractical, especially in cases where a large number of objects must be\r\nspecified. Substantial computational and storage requirements become especially acute when object orientation and scale have to\r\nbe considered. Therefore automated or semi-automated segmentation techniques are essential if these software applications are\r\never to gain widespread clinical use. The main purpose of this work is to analyze segmentation techniques for the definition of\r\nanatomical structures under telemedical systems.
Loading....