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|Contents Text: ||Over the last decade or so, many investigators have carried out basic studies and clinical applications toward the development of modern computerized schemes for detection and characterization of lesions in radiologic images, based on computer vision and artificial intelligence. These methods and techniques are generally called computer-aided diagnosis (CAD) schemes. The development of CAD has now reached a new phase, since the first commercial unit of detection of breast lesion in mammograms was approved in June 1998 by the FDA for marketing and sale for clinical use. This book, Computer-Aided Diagnosis in Medical Imaging, presents papers from the First International Workshop on Computer-Aided Diagnosis held on September, 1998 at the University of Chicago Downtown Center. The meeting provided a forum for leading researchers and practitioners in this rapidly expanding field, encompassing automated image analysis, quantitation of image information, 2D and 3D multimodality image integration, advanced image processing and artificial neural network application. Advances have been made in the computerized analysis of digital chest images, especially the detection of pulmonary nodules, using such techniques as artificial neural networks, temporal subtraction, and dual-energy imaging. Various observer performance studies have documented the benefit of radiologists using a computer aid in their interpretation process. Similar strides have been made with breast imaging with the aims of increased patient management. CAD research in breast imaging is now including digital mammography, ultrasound, and magnetic resonance imaging. Computerized enhancement, analysis and visualization of three-dimensional medical images have touched both diagnostic radiology (e.g., enhanced interpretation) and radiation therapy (e.g., treatment planning). As low-dose, spiral CT becomes routine, CT images may potentially be used for the screening of disease such as lung cancer utilizing computerized detection of pulmonary nodules in CT images of the thorax. Image segmentation and visualization techniques are being investigated as means to view representations of cardiac and abdominal structures such as in virtual colonoscopy. Vascular imaging based on either biplane, CTA, and intravascular ultrasound will benefit greatly with developed computerized methods for fusion and visualization. The efficient and effective use of CAD will depend on well implemented PACS, which will transport images, patient data, and CAD results to required sites within and about medical centers. It is evident from the Workshop that the future of computer-aided diagnosis is more promising now than ever. Continued research for improved computer image analysis methods and future clinical trials will help optimize systems, as well as determine their actual contributions to the interpretation process.|
|Title: ||Computer-Aided Diagnosis in Medical Imaging|
|Author: ||Edited by K.Doi, H.MacMahon, M.L.Gige|
|Price: ||List: 186.00 YOUR PRICE: 186.00|
|Publisher: ||EXCERPTA MEDICA|
|# of Pages: ||580|
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