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Computer Vision Techniques for the Diagnosis of Skin Cancer

SBE: COMPUTER VISION TECHNIQUES DIAGNOSIS SKIN CANCER

Medical Science & Research

Health, Medicine & Nursing

Gt Product Group

Binding Format

Marketing Imprint Name

B2B GT

CL Carton Count

Imprint Name

B2B & B2C

The goal of this volume is to summarize the state-of-the-art in the utilization of computer vision techniques in the diagnosis of skin cancer. 
Malignant melanoma is one of the most rapidly increasing cancers in the world. Early diagnosis is particularly important since melanoma can be cured with a simple excision if detected early. In recent years, dermoscopy has proved valuable in visualizing the morphological structures in pigmented lesions. However, it has also been shown that dermoscopy is difficult to learn and subjective. Newer technologies such as infrared imaging, multispectral imaging, and confocal microscopy, have recently come to the forefront in providing greater diagnostic accuracy. These imaging technologies presented in this book can serve as an adjunct to physicians and  provide automated skin cancer screening. Although computerized techniques cannot as yet provide a definitive diagnosis, they can be used to improve biopsy decision-making as well as early melanoma detection, especially for patients with multiple atypical nevi.

POST SECONDARY FOUR YEAR

COLFR

COLJR

COLSO

COLSR

Duration

Duration Unit Of Measure

Transaction Type

Front Cover.
Other Frontmatter.
Title Page.
Copyright Page.
Preface.
Contents.
1: Pigment Network Detection and Analysis.
2: Pattern Analysis in Dermoscopic Images.
3: A Bag-of-Features Approach for the Classification of Melanomas in Dermoscopy Images: The Role of Color and Texture Descriptors.
4: Automatic Diagnosis of Melanoma Based on the 7-Point Checklist.
5: Dermoscopy Image Processing for Chinese.
6: Automated Detection of Melanoma in Dermoscopic Images.
7: Melanoma Decision Support Using Lighting-Corrected Intuitive Feature Models.
8: Texture Information in Melanocytic Skin Lesion Analysis Based on Standard Camera Images.
9: Recovering Skin Reflectance and Geometry for Diagnosis of Melanoma.
10: Melanoma Diagnosis with Multiple Decision Trees.

Computer Vision Techniques for the Diagnosis of Skin Cancer.css-1p8rvzy{position:absolute;padding-left:8px;}

Computer Vision Techniques for the Diagnosis of Skin Cancer