Convolutional Neural Networks for Medical Image Processing Applications

图书简介

The rise in living standards increases the expectation of people in almost every field. At the forefront is health. Over the past few centuries, there have been major developments in healthcare. Medical device technology and developments in artificial intelligence (AI) are among the most important ones. The improving technology and our ability to harness the technology effectively by means such as AI have led to unprecedented advances, resulting in early diagnosis of diseases. AI algorithms enable the fast and early evaluation of images from medical devices to maximize the benefits. While developments in the field of AI were quickly adapted to the field of health, in some cases this contributed to the formation of innovative artificial intelligence algorithms. Today, the most effective artificial intelligence method is accepted as deep learning. Convolutional neural network (CNN) architectures are deep learning algorithms used for image processing. This book contains applications of CNN methods. The content is quite extensive, including the application of different CNN methods to various medical image processing problems. Readers will be able to analyze the effects of CNN methods presented in the book in medical applications.

Chapter 1: Ulcer and Red Lesion Detection in Wireless Capsule Endoscopy Images using CNN Said Charfi, Mohamed El Ansari, Ayoub Ellahyani, and Ilyas El Jaafari Chapter 2: Comparison of Traditional Machine Learning Algorithms and Convolution Neural Networks for Detection of Peripheral Malarial Parasites in Blood Smears Aravinda C.V., Meng Lin, Udaya Kumar Reddy K R, H N Prakash, Amar Prabhu G, and Sudeepa K.B. Chapter 3: Deep Learning-Based Computer-Aided Diagnosis System for Attention Deficit Hyperactivity Disorder Classification Using Synthetic Data Gulay Cicek, and Aydin AKAN Chapter 4: Basic Ensembles of Vanilla-Style Deep Learning Models Improve Liver Segmentation from CT Images A. Emre Kavur, Ludmila I. Kuncheva, and M. Alper Selver Chapter 5: Convolutional Neural Networks for Medical Image Analysis Rajesh Gogineni, and Ashvini Chaturvedi Chapter 6: Convolutional neural networks for segmentation in short-axis cine cardiac magnetic resonance imaging: review and considerations Manuel Pérez-Pelegrí, José V. Monmeneu, María P. López-Lereu, and David Moratal Chapter 7: Do More with Less: Deep Learning in Medical Imaging Shivani Rohilla, Mahipal Jadeja, and Emmanuel S. Pilli Chapter 8: Automatic Classification of fMRI Signals from Behavioral, Cognitive and Affective Tasks Using Deep Learning Cemre Candemir, Osman Tayfun Biskin, Mustafa Alper Selver, and Ali Saffet Gönül Chapter 9: Detection of COVID-19 in Lung CT-Scans using Reconstructed Image Features Ankita Sharma, and Preety Singh Chapter 10: Dental image analysis: Where deep learning meets d

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Convolutional Neural Networks for Medical Image Processing Applications 用于医学图像处理应用的卷积神经网络 军事医学

Convolutional Neural Networks for Medical Image Processing Applications

用于医学图像处理应用的卷积神经网络
军事医学