George Jayesh (44 results)
Language: English
Published by Success Road Enterprises, 2015
Series: The Game Changer, Book 1 of 8. Book 1 of 8 - The Game Changer
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Maples, T: GAME CHANGER
Aghay, Iman; Maples, Trevor; Sinclaire, Mahara; Chow, Jonathan; Mattiello, Lucas; Be'er, Philip; Khawaja, Tahir; Van Damme, Nicole; Verdolaga, George; Pethani, Jayesh
Language: English
Published by Amazon Digital Services LLC - KDP Print US, 2015
Series: The Game Changer, Book 1 of 8. Book 1 of 8 - The Game Changer
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Taschenbuch. Condition: Neu. Neuware - There are moments in all of our lives that cause many of us to feel tired and pushed into a corner, as if nothing is going the way we hoped. There are many of these moments that we may not appreciate at the time, but these are also the exact moments that make us stronger. These are the time…s that force us to take a leap of faith, to take a bold action that could change our lives and the lives of many people around us. This book started out as a simple writing project for each of the authors, but resulted in many life-changing transformations for the people involved. Not just the authors, but their families, our reviewers, editors, and readers. This book features 10 amazing stories of people, who at some point, felt hopeless, broken, and out of ideas to fix their problems. Yet, it was during these very moments that they all made a bold decision and embarked on a life-altering action. These are all real stories, of real people, going through real problems and making big changes.
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Language: English
Published by LAP LAMBERT Academic Publishing Mai 2018, 2018
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This Comprehensive text on CAD system for classification of breast cancer from mammogram images is designed for research scholars of biomedical image and signal processing. This book offers an introduction to Mammogram images and cl…assification of cancer from this images. Breast cancer is a leading cause of death among women and second main cause of death after lung cancer. In order to reduce unnecessary biopsies which cause patient anxiety and health care cost it is important to improve the accuracy of interpreting mammographic lesions thereby increasing the positive predictive value of mammography. Current CAD system is clinically used to serve as a second reader of breast cancer detection. Using the existing CAD, microcalcification can get better detection performance but detection performance for mass is not satisfactory. This work present a method to efficiently detect the mass abnormalities and classify the lesions as malignant or benign. The malignant lesions were further classified into types of malignant breast cancer. The proposed system uses hybrid image processing techniques for improving the accuracy of existing system. 80 pp. Englisch.
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Language: English
Published by LAP LAMBERT Academic Publishing Nov 2025, 2025
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 80 pp. Englisch.
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Language: Spanish
Published by Ediciones Nuestro Conocimiento Mrz 2023, 2023
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Este exhaustivo texto sobre el sistema CAD para la clasificación del cáncer de mama a partir de imágenes de mamografías está diseñado para investigadores en procesamiento de imágenes y señales biomédicas. Este libro ofrece una intro…ducción a las imágenes de mamografía y a la clasificación del cáncer a partir de estas imágenes. El cáncer de mama es una de las principales causas de muerte entre las mujeres y la segunda después del cáncer de pulmón. Con el fin de reducir las biopsias innecesarias que provocan ansiedad en las pacientes y costes sanitarios, es importante mejorar la precisión de la interpretación de las lesiones mamográficas, aumentando así el valor predictivo positivo de la mamografía. El sistema CAD actual se utiliza clínicamente como segundo lector para la detección del cáncer de mama. Utilizando el CAD existente, la microcalcificación puede obtener un mejor rendimiento de detección, pero el rendimiento de detección de la masa no es satisfactorio. Este trabajo presenta un método para detectar eficazmente las anomalías de masa y clasificar las lesiones como malignas o benignas. Las lesiones malignas se clasifican además en tipos de cáncer de mama maligno. El sistema propuesto utiliza técnicas híbridas de procesamiento de imágenes para mejorar la precisión del sistema existente. 76 pp. Spanisch.
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PAP. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
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PAP. Condition: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: George M. JayeshJayesh George M is Assistant Professor in Department of Electronics and Communication, Vimal Jyothi Engineering College, Kannur, Kerala. His area of specialization is Biomedical image an…d signal processing. He is a gr.
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Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermanyBuchWeltWeit Ludwig Meier e.K.
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Ce texte complet sur le système de CAO pour la classification du cancer du sein à partir d'images de mammographie est conçu pour les chercheurs en traitement d'images et de signaux biomédicaux. Ce livre propose une introduction aux…images de mammographie et à la classification des cancers à partir de ces images. Le cancer du sein est l'une des principales causes de décès chez les femmes et la deuxième cause de décès après le cancer du poumon. Afin de réduire le nombre de biopsies inutiles, source d'anxiété pour les patientes et de coûts pour les soins de santé, il est important d'améliorer la précision de l'interprétation des lésions mammographiques et d'augmenter ainsi la valeur prédictive positive de la mammographie. Le système CAD actuel est utilisé cliniquement comme second lecteur pour la détection du cancer du sein. Avec le système CAD existant, les microcalcifications peuvent être mieux détectées, mais la détection de la masse n'est pas satisfaisante. Ce travail présente une méthode permettant de détecter efficacement les anomalies de masse et de classer les lésions comme malignes ou bénignes. Les lésions malignes ont ensuite été classées en types de cancer du sein malin. Le système proposé utilise des techniques hybrides de traitement d'images pour améliorer la précision du système existant. 76 pp. Französisch.
Language: English
Published by LAP LAMBERT Academic Publishing Mai 2018, 2018
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This Comprehensive text on CAD system for classification of breast cancer from mammogram images is designed for research scholars of biomedical image and signal processing. This book offers an introduction to Mammogram images and classi…fication of cancer from this images. Breast cancer is a leading cause of death among women and second main cause of death after lung cancer. In order to reduce unnecessary biopsies which cause patient anxiety and health care cost it is important to improve the accuracy of interpreting mammographic lesions thereby increasing the positive predictive value of mammography. Current CAD system is clinically used to serve as a second reader of breast cancer detection. Using the existing CAD, microcalcification can get better detection performance but detection performance for mass is not satisfactory. This work present a method to efficiently detect the mass abnormalities and classify the lesions as malignant or benign. The malignant lesions were further classified into types of malignant breast cancer. The proposed system uses hybrid image processing techniques for improving the accuracy of existing system.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 80 pp. Englisch.
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This Comprehensive text on CAD system for classification of breast cancer from mammogram images is designed for research scholars of biomedical image and signal processing. This book offers an introduction to Mammogram images and classif…ication of cancer from this images. Breast cancer is a leading cause of death among women and second main cause of death after lung cancer. In order to reduce unnecessary biopsies which cause patient anxiety and health care cost it is important to improve the accuracy of interpreting mammographic lesions thereby increasing the positive predictive value of mammography. Current CAD system is clinically used to serve as a second reader of breast cancer detection. Using the existing CAD, microcalcification can get better detection performance but detection performance for mass is not satisfactory. This work present a method to efficiently detect the mass abnormalities and classify the lesions as malignant or benign. The malignant lesions were further classified into types of malignant breast cancer. The proposed system uses hybrid image processing techniques for improving the accuracy of existing system.
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Taschenbuch. Condition: Neu. CAD System for Classification of Breast Cancer from Mammogram Images | A complete guide for research beginners | Jayesh George M. (u. a.) | Taschenbuch | 80 S. | Englisch | 2018 | LAP LAMBERT Academic Publishing | EAN 9786139838868 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tar…pen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu Print on Demand.
Language: English
Published by LAP LAMBERT Academic Publishing Nov 2025, 2025
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This Comprehensive text on CAD system for classification of breast cancer from mammogram images is designed for research scholars of biomedical image and signal processing. This book offers an introduction to Mammogram images and classi…fication of cancer from this images. Breast cancer is a leading cause of death among women and second main cause of death after lung cancer. In order to reduce unnecessary biopsies which cause patient anxiety and health care cost it is important to improve the accuracy of interpreting mammographic lesions thereby increasing the positive predictive value of mammography. Current CAD system is clinically used to serve as a second reader of breast cancer detection. Using the existing CAD, microcalcification can get better detection performance but detection performance for mass is not satisfactory. This work present a method to efficiently detect the mass abnormalities and classify the lesions as malignant or benign. The malignant lesions were further classified into types of malignant breast cancer. The proposed system uses hybrid image processing techniques for improving the accuracy of existing system.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 80 pp. Englisch.
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Language: Spanish
Published by Ediciones Nuestro Conocimiento Mär 2023, 2023
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Este exhaustivo texto sobre el sistema CAD para la clasificación del cáncer de mama a partir de imágenes de mamografías está diseñado para investigadores en procesamiento de imágenes y señales biomédicas. Este libro ofrece una introducc…ión a las imágenes de mamografía y a la clasificación del cáncer a partir de estas imágenes. El cáncer de mama es una de las principales causas de muerte entre las mujeres y la segunda después del cáncer de pulmón. Con el fin de reducir las biopsias innecesarias que provocan ansiedad en las pacientes y costes sanitarios, es importante mejorar la precisión de la interpretación de las lesiones mamográficas, aumentando así el valor predictivo positivo de la mamografía. El sistema CAD actual se utiliza clínicamente como segundo lector para la detección del cáncer de mama. Utilizando el CAD existente, la microcalcificación puede obtener un mejor rendimiento de detección, pero el rendimiento de detección de la masa no es satisfactorio. Este trabajo presenta un método para detectar eficazmente las anomalías de masa y clasificar las lesiones como malignas o benignas. Las lesiones malignas se clasifican además en tipos de cáncer de mama maligno. El sistema propuesto utiliza técnicas híbridas de procesamiento de imágenes para mejorar la precisión del sistema existente.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 76 pp. Spanisch.
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Este exhaustivo texto sobre el sistema CAD para la clasificación del cáncer de mama a partir de imágenes de mamografías está diseñado para investigadores en procesamiento de imágenes y señales biomédicas. Este libro ofrece una introducci…ón a las imágenes de mamografía y a la clasificación del cáncer a partir de estas imágenes. El cáncer de mama es una de las principales causas de muerte entre las mujeres y la segunda después del cáncer de pulmón. Con el fin de reducir las biopsias innecesarias que provocan ansiedad en las pacientes y costes sanitarios, es importante mejorar la precisión de la interpretación de las lesiones mamográficas, aumentando así el valor predictivo positivo de la mamografía. El sistema CAD actual se utiliza clínicamente como segundo lector para la detección del cáncer de mama. Utilizando el CAD existente, la microcalcificación puede obtener un mejor rendimiento de detección, pero el rendimiento de detección de la masa no es satisfactorio. Este trabajo presenta un método para detectar eficazmente las anomalías de masa y clasificar las lesiones como malignas o benignas. Las lesiones malignas se clasifican además en tipos de cáncer de mama maligno. El sistema propuesto utiliza técnicas híbridas de procesamiento de imágenes para mejorar la precisión del sistema existente.
Language: Portuguese
Published by Edições Nosso Conhecimento Mrz 2023, 2023
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Este texto compreensivo sobre o sistema CAD para classificação do cancro da mama a partir de imagens de mamografia foi concebido para estudiosos da investigação de imagem biomédica e processamento de sinais. Este livro oferece uma i…ntrodução às imagens de Mamografia e classificação do cancro a partir destas imagens. O cancro da mama é uma das principais causas de morte entre as mulheres e a segunda principal causa de morte após o cancro do pulmão. A fim de reduzir biópsias desnecessárias que causam ansiedade e custos de cuidados de saúde do paciente, é importante melhorar a exactidão da interpretação das lesões mamográficas, aumentando assim o valor preditivo positivo da mamografia. O actual sistema CAD é clinicamente utilizado para servir como segundo leitor de detecção do cancro da mama. Utilizando o CAD existente, a microcalcificação pode obter um melhor desempenho de detecção, mas o desempenho de detecção de massa não é satisfatório. Este trabalho apresenta um método para detectar eficazmente as anomalias de massa e classificar as lesões como malignas ou benignas. As lesões malignas foram ainda classificadas em tipos de cancro maligno da mama. O sistema proposto utiliza técnicas híbridas de processamento de imagem para melhorar a precisão do sistema existente. 72 pp. Portugiesisch.
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Dieser umfassende Text über ein CAD-System zur Klassifizierung von Brustkrebs anhand von Mammogrammbildern richtet sich an Forscher im Bereich biomedizinische Bild- und Signalverarbeitung. Dieses Buch bietet eine Einführung in Mammo…grammbilder und die Klassifizierung von Krebs anhand dieser Bilder. Brustkrebs ist eine der häufigsten Todesursachen bei Frauen und die zweithäufigste Todesursache nach Lungenkrebs. Um unnötige Biopsien zu vermeiden, die die Patientinnen verunsichern und die Gesundheitskosten in die Höhe treiben, ist es wichtig, die Genauigkeit der Interpretation von mammographischen Läsionen zu verbessern und damit den positiven Vorhersagewert der Mammographie zu erhöhen. Das derzeitige CAD-System wird klinisch als zweites Lesegerät für die Brustkrebserkennung eingesetzt. Mit dem bestehenden CAD-System können Mikroverkalkungen besser erkannt werden, aber die Erkennungsleistung für Massen ist nicht zufriedenstellend. In dieser Arbeit wird eine Methode zur effizienten Erkennung von Massenanomalien und zur Klassifizierung der Läsionen als bösartig oder gutartig vorgestellt. Die bösartigen Läsionen wurden weiter in Arten von bösartigem Brustkrebs klassifiziert. Das vorgeschlagene System verwendet hybride Bildverarbeitungstechniken, um die Genauigkeit des bestehenden Systems zu verbessern. 76 pp. Deutsch.
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Questo testo completo sul sistema CAD per la classificazione del cancro al seno dalle immagini mammografiche è stato progettato per gli studiosi di ricerca sull'elaborazione delle immagini e dei segnali biomedici. Questo libro offre… un'introduzione alle immagini mammografiche e alla classificazione del cancro da queste immagini. Il cancro al seno è una delle principali cause di morte tra le donne e la seconda causa di morte dopo il cancro ai polmoni. Per ridurre le biopsie non necessarie, che causano ansia alle pazienti e costi sanitari, è importante migliorare l'accuratezza dell'interpretazione delle lesioni mammografiche, aumentando così il valore predittivo positivo della mammografia. L'attuale sistema CAD viene utilizzato clinicamente come secondo lettore per la diagnosi del cancro al seno. Utilizzando il CAD esistente, le microcalcificazioni possono ottenere prestazioni di rilevamento migliori, ma le prestazioni di rilevamento della massa non sono soddisfacenti. Questo lavoro presenta un metodo per rilevare in modo efficiente le anomalie di massa e classificare le lesioni come maligne o benigne. Le lesioni maligne sono state ulteriormente classificate in tipi di cancro al seno maligno. Il sistema proposto utilizza tecniche ibride di elaborazione delle immagini per migliorare l'accuratezza del sistema esistente. 72 pp. Italienisch.
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