Color Medical Image Analysis [electronic resource] / edited by M. Emre Celebi, Gerald Schaefer.

By: Celebi, M. Emre [editor.]Contributor(s): Schaefer, Gerald [editor.] | SpringerLink (Online service)Material type: TextTextLanguage: English Series: Lecture Notes in Computational Vision and Biomechanics: 6Publisher: Dordrecht : Springer Netherlands : Imprint: Springer, 2013Description: X, 204 p. 69 illus., 63 illus. in color. online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9789400753891Subject(s): Engineering | Radiology, Medical | Computer vision | Biomedical engineering | Engineering | Biomedical Engineering | Image Processing and Computer Vision | Imaging / RadiologyAdditional physical formats: Printed edition:: No titleDDC classification: 610.28 LOC classification: R856-857Online resources: Click here to access online In: Springer eBooksSummary: Since the early 20th century, medical imaging has been dominated by monochrome imaging modalities such as x-ray, computed tomography, ultrasound, and magnetic resonance imaging. As a result, color information has been overlooked in medical image analysis applications. Recently, various medical imaging modalities that involve color information have been introduced. These include cervicography, dermoscopy, fundus photography, gastrointestinal endoscopy, microscopy, and wound photography. However, in comparison to monochrome images, the analysis of color images is a relatively unexplored area. The multivariate nature of color image data presents new challenges for researchers and practitioners as the numerous methods developed for monochrome images are often not directly applicable to multichannel images. The goal of this volume is to summarize the state-of-the-art in the utilization of color information in medical image analysis.
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Since the early 20th century, medical imaging has been dominated by monochrome imaging modalities such as x-ray, computed tomography, ultrasound, and magnetic resonance imaging. As a result, color information has been overlooked in medical image analysis applications. Recently, various medical imaging modalities that involve color information have been introduced. These include cervicography, dermoscopy, fundus photography, gastrointestinal endoscopy, microscopy, and wound photography. However, in comparison to monochrome images, the analysis of color images is a relatively unexplored area. The multivariate nature of color image data presents new challenges for researchers and practitioners as the numerous methods developed for monochrome images are often not directly applicable to multichannel images. The goal of this volume is to summarize the state-of-the-art in the utilization of color information in medical image analysis.

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