| Description |
1 online resource |
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text txt rdacontent |
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computer c rdamedia |
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online resource cr rdacarrier |
| Summary |
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. |
| Subject |
Brain -- Magnetic resonance imaging.
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Brain -- Tumors.
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Brain Neoplasms |
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Cerveau -- Imagerie par résonance magnétique.
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Cerveau -- Tumeurs.
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Brain -- Magnetic resonance imaging
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Brain -- Tumors
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| Added Author |
Chaki, Jyotismita, editor.
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| Other Form: |
Print version: 9780323911719 |
| ISBN |
9780323983952 (electronic book) |
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0323983952 (electronic book) |
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9780323911719 (electronic bk.) |
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0323911714 (electronic bk.) |
| Standard No. |
UKMGB 020328044 |
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AU@ 000070396649 |
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