The utilization of image processing and computer vision technologies has shown remarkable efficacy in analyzing kidney ultrasound images for the recognition of kidney stone related problems. The motivation for this research is the increasing prevalence of kidney disease worldwide, which is a serious health issue. The study focuses on kidney stones, a common and painful condition requiring timely and accurate diagnosis. Ultrasound imaging, preferred for its non-invasive, radiation-free, and cost-effective nature, often suffers from speckle noise and low contrast, complicating the accurate identification and classification of kidney stones. This underscores the need for enhanced image processing techniques to improve ultrasound image quality and diagnostic value. By adopting a comprehensive approach that includes image acquisition, pre-processing, feature extraction, and classification, the research aims to develop an automatic system for reliable and accurate kidney stone detection. The ultimate goal is to create a robust computer-aided detection system that aids medical professionals by reducing diagnostic burden, minimizing errors and enhancing the efficiency of stone detection.
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Paperback. Etat : new. Paperback. The utilization of image processing and computer vision technologies has shown remarkable efficacy in analyzing kidney ultrasound images for the recognition of kidney stone related problems. The motivation for this research is the increasing prevalence of kidney disease worldwide, which is a serious health issue. The study focuses on kidney stones, a common and painful condition requiring timely and accurate diagnosis. Ultrasound imaging, preferred for its non-invasive, radiation-free, and cost-effective nature, often suffers from speckle noise and low contrast, complicating the accurate identification and classification of kidney stones. This underscores the need for enhanced image processing techniques to improve ultrasound image quality and diagnostic value. By adopting a comprehensive approach that includes image acquisition, pre-processing, feature extraction, and classification, the research aims to develop an automatic system for reliable and accurate kidney stone detection. The ultimate goal is to create a robust computer-aided detection system that aids medical professionals by reducing diagnostic burden, minimizing errors and enhancing the efficiency of stone detection. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N° de réf. du vendeur 9786209138188
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Taschenbuch. Etat : Neu. Ultrasound Image Analysis for Detection and Study of Kidney Stones | DEVELOPMENT OF SYSTEM FOR DETECTION OF KIDNEY STONES AND THEIR CHARACTERISTICS IN ULTRASOUND IMAGES | Gurjeet Kaur (u. a.) | Taschenbuch | Englisch | 2025 | LAP LAMBERT Academic Publishing | EAN 9786209138188 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu. N° de réf. du vendeur 134318707
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Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -The utilization of image processing and computer vision technologies has shown remarkable efficacy in analyzing kidney ultrasound images for the recognition of kidney stone related problems. The motivation for this research is the increasing prevalence of kidney disease worldwide, which is a serious health issue. The study focuses on kidney stones, a common and painful condition requiring timely and accurate diagnosis. Ultrasound imaging, preferred for its non-invasive, radiation-free, and cost-effective nature, often suffers from speckle noise and low contrast, complicating the accurate identification and classification of kidney stones. This underscores the need for enhanced image processing techniques to improve ultrasound image quality and diagnostic value. By adopting a comprehensive approach that includes image acquisition, pre-processing, feature extraction, and classification, the research aims to develop an automatic system for reliable and accurate kidney stone detection. The ultimate goal is to create a robust computer-aided detection system that aids medical professionals by reducing diagnostic burden, minimizing errors and enhancing the efficiency of stone detection.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 168 pp. Englisch. N° de réf. du vendeur 9786209138188
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