9786204737188 - mri-based brain tumor analysis system: a deep learning approach di thiruvenkadam, kalaiselvi; thiyagarajan, padmapriya (5 risultati)

- Brossura
Da: preigu, Osnabrück, Germaniapreigu
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 39,45
EUR 70,00 spedizioneSpedito da Germania a U.S.A.Quantità: 5 disponibili
Taschenbuch. Condizione: Neu. MRI-based Brain Tumor Analysis System | A Deep Learning Approach | Kalaiselvi Thiruvenkadam (u. a.) | Taschenbuch | Englisch | 2022 | LAP LAMBERT Academic Publishing | EAN 9786204737188 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preig…u[dot]de | Anbieter: preigu.

- Brossura
- Print on Demand
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 43,90
EUR 23,00 spedizioneSpedito da Germania a U.S.A.Quantità: 2 disponibili
Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book is the outcome of our research practice over 15 years in the area of brain tumor image analysis using computational intelligence techniques. Many automatic methods were developed and published in reputed international jou…rnals. Currently, deep learning-based models are targeted to classify brain tumors from magnetic resonance imaging (MRI) human head scans. This book is primarily focused on the development of an MRI-based brain tumor analysis system using a deep learning approach. This book is organized into five chapters. Chapter 1 describes the significance of medical image processing, the principles and role of MRI in medical image analysis and the importance of artificial intelligence (AI) systems. Chapter 2 explains the anatomy of the brain, the cause of brain tumor and its types. Chapter 3 describes the rudiments of deep learning (DL) techniques such as machine learning (ML) basics, algorithms, evolution, role in tumor imaging, the architecture of deep neural networks (DNN) and convolutional neural networks (CNN). Chapter 4 explains the development of the proposed DL tool of brain tumor analysis. Finally, chapter 5 concludes with further works in future. 56 pp. Englisch.

- Brossura
- Print on Demand
Da: moluna, Greven, Germaniamoluna
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 37,23
EUR 48,99 spedizioneSpedito da Germania a U.S.A.Quantità: Più di 20 disponibili
Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book is the outcome of our research practice over 15 years in the area of brain tumor image analysis using computational intelligence techniques. Many automatic methods were developed and published in reputed in…ternational journals. Currently, deep lea.

- Brossura
- Print on Demand
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 43,90
EUR 60,00 spedizioneSpedito da Germania a U.S.A.Quantità: 1 disponibili
Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book is the outcome of our research practice over 15 years in the area of brain tumor image analysis using computational intelligence techniques. Many automatic methods were developed and published in reputed international journal…s. Currently, deep learning-based models are targeted to classify brain tumors from magnetic resonance imaging (MRI) human head scans. This book is primarily focused on the development of an MRI-based brain tumor analysis system using a deep learning approach. This book is organized into five chapters. Chapter 1 describes the significance of medical image processing, the principles and role of MRI in medical image analysis and the importance of artificial intelligence (AI) systems. Chapter 2 explains the anatomy of the brain, the cause of brain tumor and its types. Chapter 3 describes the rudiments of deep learning (DL) techniques such as machine learning (ML) basics, algorithms, evolution, role in tumor imaging, the architecture of deep neural networks (DNN) and convolutional neural networks (CNN). Chapter 4 explains the development of the proposed DL tool of brain tumor analysis. Finally, chapter 5 concludes with further works in future.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 56 pp. Englisch.

- Brossura
- Print on Demand
Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 44,59
EUR 60,51 spedizioneSpedito da Germania a U.S.A.Quantità: 1 disponibili
Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book is the outcome of our research practice over 15 years in the area of brain tumor image analysis using computational intelligence techniques. Many automatic methods were developed and published in reputed international journals…. Currently, deep learning-based models are targeted to classify brain tumors from magnetic resonance imaging (MRI) human head scans. This book is primarily focused on the development of an MRI-based brain tumor analysis system using a deep learning approach. This book is organized into five chapters. Chapter 1 describes the significance of medical image processing, the principles and role of MRI in medical image analysis and the importance of artificial intelligence (AI) systems. Chapter 2 explains the anatomy of the brain, the cause of brain tumor and its types. Chapter 3 describes the rudiments of deep learning (DL) techniques such as machine learning (ML) basics, algorithms, evolution, role in tumor imaging, the architecture of deep neural networks (DNN) and convolutional neural networks (CNN). Chapter 4 explains the development of the proposed DL tool of brain tumor analysis. Finally, chapter 5 concludes with further works in future.