| Description |
1 online resource |
| Contents |
Front Cover -- Artificial Intelligence and Image Processing in Medical Imaging -- Copyright Page -- Contents -- List of contributors -- 1 Introduction to machine learning and artificial intelligence -- 1.1 Comprehensive introduction to machine learning and artificial intelligence -- 1.1.1 Types of machine learning -- 1.1.2 Machine learning algorithm -- 1.1.2.1 Support vector machine -- 1.1.2.2 Logistic regression -- 1.1.2.3 Linear regression -- 1.1.2.4 K-means clustering -- 1.1.2.5 K-nearest neighbor -- 1.1.2.6 Decision tree -- 1.1.2.7 Random forest -- 1.1.3 Deep learning |
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1.1.4 Terminologies in machine learning -- 1.1.4.1 Bias and variance -- 1.1.4.2 Overfitting and underfitting -- 1.1.4.3 Principal component analysis -- 1.1.4.4 Cross-validation -- 1.1.4.5 Gradient descent -- 1.1.4.6 Cost function -- 1.1.4.7 Parameter and hyperparameter -- 1.1.4.8 Transfer learning -- 1.1.4.9 Performance evaluation matrix -- References -- 2 Convolution neural network and deep learning -- Abbreviations -- 2.1 Brief history of deep learning -- 2.2 Deep learning -- 2.2.1 Convolution neural network -- 2.2.1.1 The basic architecture of the convolutional neural network |
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2.2.1.1.1 Convolutional layer -- 2.2.1.1.2 Pooling layer -- 2.2.1.1.3 Fully connected layer -- 2.2.2 Common convolutional neural network models -- 2.2.2.1 AlexNet -- 2.2.2.2 VGG16 -- 2.2.2.3 ResNet50 -- 2.2.2.4 InceptionV3 -- 2.2.2.5 EfficientNet -- 2.2.3 Applications of convolutional neural networks -- 2.3 Common terminologies in deep learning -- 2.3.1 Neural network -- 2.3.2 Recurrent neural network -- 2.3.3 Generative adversarial network -- 2.3.4 Back-propagation -- 2.3.5 Gradient descent -- 2.3.6 Activation function -- 2.3.7 Overfitting -- 2.3.8 Batch normalization -- 2.3.9 Transfer learning |
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2.3.10 Autoencoder -- 2.3.11 Restricted Boltzmann machine -- 2.3.12 Convolutional layer -- 2.3.13 Pooling layer -- 2.3.14 Fully connected layer -- 2.3.15 Embedding layer -- 2.3.16 Cross-entropy -- 2.3.17 Optimizer -- 2.3.18 Back-propagation through time -- 2.3.19 Batch size -- 2.3.20 Epoch -- 2.3.21 Vanishing gradient -- 2.3.22 Strides -- 2.3.23 Padding -- 2.3.24 Hyperparameter -- 2.3.25 Filters -- 2.3.26 Dropout -- References -- 3 Image preprocessing phase with artificial intelligence methods on medical images -- 3.1 Introduction -- 3.2 Medical imaging -- 3.3 Image processing |
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3.4 Histogram equalization -- 3.5 Power-law transformation -- 3.6 Linear transformation -- 3.7 Log transformation -- 3.8 Mean filter -- 3.9 Median filter -- 3.10 Gaussian filter -- 3.11 Image compression -- 3.12 Image enhancement -- 3.13 Image resizing -- 3.14 Image restoration -- 3.15 Image segmentation -- 3.16 Artificial intelligence in medical imaging -- 3.17 Applications of image preprocessing in medical imaging -- 3.18 Simplified: applications of artificial intelligence and image preprocessing in medical imaging -- 3.19 Medical cases -- 3.19.1 Lung cancer-computed tomography scans |
| Notes |
Machine-generated record |
| Form |
Electronic book
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| ISBN |
9780323954631 |
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0323954634 |
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