Ebook: Color Medical Image Analysis

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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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.

Content:
Front Matter....Pages I-X
A Data Driven Approach to Cervigram Image Analysis and Classification....Pages 1-13
Macroscopic Pigmented Skin Lesion Segmentation and Its Influence on Lesion Classification and Diagnosis....Pages 15-39
Color and Spatial Features Integrated Normalized Distance for Density Based Border Detection in Dermoscopy Images....Pages 41-61
A Color and Texture Based Hierarchical K-NN Approach to the Classification of Non-melanoma Skin Lesions....Pages 63-86
Color Quantization of Dermoscopy Images Using the K-Means Clustering Algorithm....Pages 87-107
Grading the Severity of Diabetic Macular Edema Cases Based on Color Eye Fundus Images....Pages 109-127
Colour Image Analysis of Wireless Capsule Endoscopy Video: A Review....Pages 129-144
Automated Prototype Generation for Multi-color Karyotyping....Pages 145-163
Colour Model Analysis for Histopathology Image Processing....Pages 165-180
A Review on CAD Tools for Burn Diagnosis....Pages 181-202
Back Matter....Pages 203-204

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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.

Content:
Front Matter....Pages I-X
A Data Driven Approach to Cervigram Image Analysis and Classification....Pages 1-13
Macroscopic Pigmented Skin Lesion Segmentation and Its Influence on Lesion Classification and Diagnosis....Pages 15-39
Color and Spatial Features Integrated Normalized Distance for Density Based Border Detection in Dermoscopy Images....Pages 41-61
A Color and Texture Based Hierarchical K-NN Approach to the Classification of Non-melanoma Skin Lesions....Pages 63-86
Color Quantization of Dermoscopy Images Using the K-Means Clustering Algorithm....Pages 87-107
Grading the Severity of Diabetic Macular Edema Cases Based on Color Eye Fundus Images....Pages 109-127
Colour Image Analysis of Wireless Capsule Endoscopy Video: A Review....Pages 129-144
Automated Prototype Generation for Multi-color Karyotyping....Pages 145-163
Colour Model Analysis for Histopathology Image Processing....Pages 165-180
A Review on CAD Tools for Burn Diagnosis....Pages 181-202
Back Matter....Pages 203-204
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