Brain Tumor MRI Image Segmentation Using Deep Learning Techniques (häftad, eng)
Brain Tumor MRI Image Segmentation Using Deep Learning Techniques offers a description of deep learning approaches used for the segmentation...
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Brain Tumor MRI Image Segmentation Using Deep Learning Techniques offers a description of deep learning approaches used for the segmentation of brain tumors. The book demonstrates core concepts of deep learning algorithms by using diagrams, data tables and examples to illustrate brain tumor segmentation.
After introducing basic concepts of deep learning-based brain tumor segmentation, sections cover techniques for modeling, segmentation and properties. A focus is placed on the application of different types of convolutional neural networks, like single path, multi path, fully convolutional network, cascade convolutional neural networks, Long Short-Term Memory - Recurrent Neural Network and Gated Recurrent Units, and more.
The book also highlights how the use of deep neural networks can address new questions and protocols, as well as improve upon existing challenges in brain tumor segmentation.
After introducing basic concepts of deep learning-based brain tumor segmentation, sections cover techniques for modeling, segmentation and properties. A focus is placed on the application of different types of convolutional neural networks, like single path, multi path, fully convolutional network, cascade convolutional neural networks, Long Short-Term Memory - Recurrent Neural Network and Gated Recurrent Units, and more.
The book also highlights how the use of deep neural networks can address new questions and protocols, as well as improve upon existing challenges in brain tumor segmentation.
Format | Häftad |
Omfång | 258 sidor |
Språk | Engelska |
Förlag | Elsevier Science & Technology |
Utgivningsdatum | 2021-12-02 |
ISBN | 9780323911719 |
Böcker
- Format Häftad
- Antal sidor 258
- Språk Engelska
- Utgivningsdatum 2021-12-02
- ISBN 9780323911719
- Förlag Elsevier Science & Technology
Specifikation
Böcker
- Format Häftad
- Antal sidor 258
- Språk Engelska
- Utgivningsdatum 2021-12-02
- ISBN 9780323911719
- Förlag Elsevier Science & Technology