Detection of Non-Melanoma Skin Cancer Using Texture Analysis
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Detection of Non-Melanoma Skin Cancer Using Texture Analysis (2014)
DE PB NW RP
ISBN: 9783659626630 bzw. 3659626635, in Deutsch, LAP Lambert Academic Publishing Dez 2014, Taschenbuch, neu, Nachdruck.
Von Händler/Antiquariat, AHA-BUCH GmbH [51283250], Einbeck, NDS, Germany.
This item is printed on demand - Print on Demand Titel. Neuware - Today, cancer constitutes a major health problem. Approximately one out of every two men and one out of every three women get cancer at some point during their lifetime. The chance of curing cancer primarily relies on its early diagnosis and the selection of its treatment depends on its malignancy level. Skin cancer is the most common form of human cancer. The annual rates of all forms of skin cancer are increasing each year. This book is aimed to develop a system that determines whether a given skin lesion microscopic image is normal, or benign tumor, or malignant tumor which can be squamous cell carcinoma, or basal cell carcinoma (the two leading skin cancer types).The proposed system passes through two main phases: training phase and testing phase. For both of them, the system implies three main stages (i.e., pre-processing, partitioning & feature extraction).In this research work, two recognition systems have been employed. The first system is based on using minimum distance classification method (MDC) to make recognition decision, while the second was based on the feed forward neural network. 148 pp. Englisch.
This item is printed on demand - Print on Demand Titel. Neuware - Today, cancer constitutes a major health problem. Approximately one out of every two men and one out of every three women get cancer at some point during their lifetime. The chance of curing cancer primarily relies on its early diagnosis and the selection of its treatment depends on its malignancy level. Skin cancer is the most common form of human cancer. The annual rates of all forms of skin cancer are increasing each year. This book is aimed to develop a system that determines whether a given skin lesion microscopic image is normal, or benign tumor, or malignant tumor which can be squamous cell carcinoma, or basal cell carcinoma (the two leading skin cancer types).The proposed system passes through two main phases: training phase and testing phase. For both of them, the system implies three main stages (i.e., pre-processing, partitioning & feature extraction).In this research work, two recognition systems have been employed. The first system is based on using minimum distance classification method (MDC) to make recognition decision, while the second was based on the feed forward neural network. 148 pp. Englisch.
2
Detection of Non-Melanoma Skin Cancer Using Texture Analysis
DE NW
ISBN: 9783659626630 bzw. 3659626635, in Deutsch, neu.
Lieferung aus: Deutschland, zzgl. Versandkosten.
Today, cancer constitutes a major health problem. Approximately one out of every two men and one out of every three women get cancer at some point during their lifetime. The chance of curing cancer primarily relies on its early diagnosis and the selection of its treatment depends on its malignancy level. Skin cancer is the most common form of human cancer. The annual rates of all forms of skin cancer are increasing each year. This book is aimed to develop a system that determines whether a given skin lesion microscopic image is normal, or benign tumor, or malignant tumor which can be squamous cell carcinoma, or basal cell carcinoma (the two leading skin cancer types).The proposed system passes through two main phases: training phase and testing phase. For both of them, the system implies three main stages (i.e., pre-processing, partitioning & feature extraction).In this research work, two recognition systems have been employed. The first system is based on using minimum distance classification method (MDC) to make recognition decision, while the second was based on the feed forward neural network.
Today, cancer constitutes a major health problem. Approximately one out of every two men and one out of every three women get cancer at some point during their lifetime. The chance of curing cancer primarily relies on its early diagnosis and the selection of its treatment depends on its malignancy level. Skin cancer is the most common form of human cancer. The annual rates of all forms of skin cancer are increasing each year. This book is aimed to develop a system that determines whether a given skin lesion microscopic image is normal, or benign tumor, or malignant tumor which can be squamous cell carcinoma, or basal cell carcinoma (the two leading skin cancer types).The proposed system passes through two main phases: training phase and testing phase. For both of them, the system implies three main stages (i.e., pre-processing, partitioning & feature extraction).In this research work, two recognition systems have been employed. The first system is based on using minimum distance classification method (MDC) to make recognition decision, while the second was based on the feed forward neural network.
3
Detection of Non-Melanoma Skin Cancer Using Texture Analysis
~EN NW AB
ISBN: 9783659626630 bzw. 3659626635, vermutlich in Englisch, neu, Hörbuch.
Lieferung aus: Niederlande, Lieferzeit: 5 Tage, zzgl. Versandkosten.
Today, cancer constitutes a major health problem. Approximately one out of every two men and one out of every three women get cancer at some point during their lifetime. The chance of curing cancer primarily relies on its early diagnosis and the selection of its treatment depends on its malignancy level. Skin cancer is the most common form of human cancer. The annual rates of all forms of skin cancer are increasing each year. This book is aimed to develop a system that determines whether a given skin lesion microscopic image is normal, or benign tumor, or malignant tumor which can be squamous cell carcinoma, or basal cell carcinoma (the two leading skin cancer types).The proposed system passes through two main phases: training phase and testing phase. For both of them, the system implies three main stages (i.e., pre-processing, partitioning & feature extraction).In this research work, two recognition systems have been employed. The first system is based on using minimum distance classification method (MDC) to make recognition decision, while the second was based on the feed forward neural network.
Today, cancer constitutes a major health problem. Approximately one out of every two men and one out of every three women get cancer at some point during their lifetime. The chance of curing cancer primarily relies on its early diagnosis and the selection of its treatment depends on its malignancy level. Skin cancer is the most common form of human cancer. The annual rates of all forms of skin cancer are increasing each year. This book is aimed to develop a system that determines whether a given skin lesion microscopic image is normal, or benign tumor, or malignant tumor which can be squamous cell carcinoma, or basal cell carcinoma (the two leading skin cancer types).The proposed system passes through two main phases: training phase and testing phase. For both of them, the system implies three main stages (i.e., pre-processing, partitioning & feature extraction).In this research work, two recognition systems have been employed. The first system is based on using minimum distance classification method (MDC) to make recognition decision, while the second was based on the feed forward neural network.
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Detection of Non-Melanoma Skin Cancer Using Texture Analysis - Design and Implementation
DE PB NW
ISBN: 9783659626630 bzw. 3659626635, in Deutsch, LAP Lambert Academic Publishing, Taschenbuch, neu.
Lieferung aus: Deutschland, Versandkostenfrei.
Detection of Non-Melanoma Skin Cancer Using Texture Analysis: Today, cancer constitutes a major health problem. Approximately one out of every two men and one out of every three women get cancer at some point during their lifetime. The chance of curing cancer primarily relies on its early diagnosis and the selection of its treatment depends on its malignancy level. Skin cancer is the most common form of human cancer. The annual rates of all forms of skin cancer are increasing each year. This book is aimed to develop a system that determines whether a given skin lesion microscopic image is normal, or benign tumor, or malignant tumor which can be squamous cell carcinoma, or basal cell carcinoma (the two leading skin cancer types).The proposed system passes through two main phases: training phase and testing phase. For both of them, the system implies three main stages (i.e., pre-processing, partitioning & feature extraction).In this research work, two recognition systems have been employed. The first system is based on using minimum distance classification method (MDC) to make recognition decision, while the second was based on the feed forward neural network. Englisch, Taschenbuch.
Detection of Non-Melanoma Skin Cancer Using Texture Analysis: Today, cancer constitutes a major health problem. Approximately one out of every two men and one out of every three women get cancer at some point during their lifetime. The chance of curing cancer primarily relies on its early diagnosis and the selection of its treatment depends on its malignancy level. Skin cancer is the most common form of human cancer. The annual rates of all forms of skin cancer are increasing each year. This book is aimed to develop a system that determines whether a given skin lesion microscopic image is normal, or benign tumor, or malignant tumor which can be squamous cell carcinoma, or basal cell carcinoma (the two leading skin cancer types).The proposed system passes through two main phases: training phase and testing phase. For both of them, the system implies three main stages (i.e., pre-processing, partitioning & feature extraction).In this research work, two recognition systems have been employed. The first system is based on using minimum distance classification method (MDC) to make recognition decision, while the second was based on the feed forward neural network. Englisch, Taschenbuch.
7
Detection of Non-Melanoma Skin Cancer Using Texture Analysis (2014)
~EN PB NW
ISBN: 9783659626630 bzw. 3659626635, vermutlich in Englisch, Taschenbuch, neu.
Lieferung aus: Deutschland, Next Day, Versandkostenfrei.
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
8
Detection of Non-Melanoma Skin C (2014)
DE PB NW
ISBN: 9783659626630 bzw. 3659626635, in Deutsch, Taschenbuch, neu.
Lieferung aus: Deutschland, Next Day, Versandkostenfrei.
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
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