Convolutional Neural Networks for Medical Applications (eBook)
XI, 96 Seiten
Springer Nature Singapore (Verlag)
978-981-19-8814-1 (ISBN)
Convolutional Neural Networks for Medical Applications consists of research investigated by the author, containing state-of-the-art knowledge, authored by Dr Teoh Teik Toe, in applying Convolutional Neural Networks (CNNs) to the medical imagery domain. This book will expose researchers to various applications and techniques applied with deep learning on medical images, as well as unique techniques to enhance the performance of these networks.Through the various chapters and topics covered, this book provides knowledge about the fundamentals of deep learning to a common reader while allowing a research scholar to identify some futuristic problem areas. The topics covered include brain tumor classification, pneumonia image classification, white blood cell classification, skin cancer classification and diabetic retinopathy detection. The first chapter will begin by introducing various topics used in training CNNs to help readers with common concepts covered across the book. Each chapter begins by providing information about the disease, its implications to the affected and how the use of CNNs can help to tackle issues faced in healthcare. Readers would be exposed to various performance enhancement techniques, which have been tried and tested successfully, such as specific data augmentations and image processing techniques utilized to improve the accuracy of the models.
Dr Teoh has been an experienced researcher in Big Data, Deep Learning, Cyber-security, Artificial Intelligence, Machine Learning and Software Development for more than 25 years. His works have been published in more than 50 journals, conferences, books and book chapters. His qualifications include a PhD in Computer Engineering from NTU, Doctor of Business Administration from University of NewCastle, Master of Law from NUS, LLB and LLM from UoL, CFA, ACCA and CIMA. He has more than 15 years of experience in data mining, quantitative analysis, data statistics, finance, accounting and law and is highly passionate about the use of deep learning to improve lives.
Convolutional Neural Networks for Medical Applications consists of research investigated by the author, containing state-of-the-art knowledge, authored by Dr Teoh Teik Toe, in applying Convolutional Neural Networks (CNNs) to the medical imagery domain. This book will expose researchers to various applications and techniques applied with deep learning on medical images, as well as unique techniques to enhance the performance of these networks.Through the various chapters and topics covered, this book provides knowledge about the fundamentals of deep learning to a common reader while allowing a research scholar to identify some futuristic problem areas. The topics covered include brain tumor classification, pneumonia image classification, white blood cell classification, skin cancer classification and diabetic retinopathy detection. The first chapter will begin by introducing various topics used in training CNNs to help readers with common concepts covered across the book. Each chapter begins by providing information about the disease, its implications to the affected and how the use of CNNs can help to tackle issues faced in healthcare. Readers would be exposed to various performance enhancement techniques, which have been tried and tested successfully, such as specific data augmentations and image processing techniques utilized to improve the accuracy of the models.
| Erscheint lt. Verlag | 23.3.2023 |
|---|---|
| Reihe/Serie | SpringerBriefs in Computer Science |
| Zusatzinfo | XI, 96 p. 1 illus. |
| Sprache | englisch |
| Themenwelt | Informatik ► Grafik / Design ► Digitale Bildverarbeitung |
| Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
| Medizin / Pharmazie ► Allgemeines / Lexika | |
| Technik ► Elektrotechnik / Energietechnik | |
| Schlagworte | Artificial Intelligence • brain tumor • computer vision • convolutional neural networks • Diabetes • Healthcare • machine learning • Medical Imagery • Neural networks • Pneumonia • skin cancer • White Blood Cells |
| ISBN-10 | 981-19-8814-5 / 9811988145 |
| ISBN-13 | 978-981-19-8814-1 / 9789811988141 |
| Haben Sie eine Frage zum Produkt? |
PDF (Wasserzeichen)Größe: 4,8 MB
DRM: Digitales Wasserzeichen
Dieses eBook enthält ein digitales Wasserzeichen und ist damit für Sie personalisiert. Bei einer missbräuchlichen Weitergabe des eBooks an Dritte ist eine Rückverfolgung an die Quelle möglich.
Dateiformat: PDF (Portable Document Format)
Mit einem festen Seitenlayout eignet sich die PDF besonders für Fachbücher mit Spalten, Tabellen und Abbildungen. Eine PDF kann auf fast allen Geräten angezeigt werden, ist aber für kleine Displays (Smartphone, eReader) nur eingeschränkt geeignet.
Systemvoraussetzungen:
PC/Mac: Mit einem PC oder Mac können Sie dieses eBook lesen. Sie benötigen dafür einen PDF-Viewer - z.B. den Adobe Reader oder Adobe Digital Editions.
eReader: Dieses eBook kann mit (fast) allen eBook-Readern gelesen werden. Mit dem amazon-Kindle ist es aber nicht kompatibel.
Smartphone/Tablet: Egal ob Apple oder Android, dieses eBook können Sie lesen. Sie benötigen dafür einen PDF-Viewer - z.B. die kostenlose Adobe Digital Editions-App.
Buying eBooks from abroad
For tax law reasons we can sell eBooks just within Germany and Switzerland. Regrettably we cannot fulfill eBook-orders from other countries.
aus dem Bereich
