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Brain Tumor MRI Image Segmentation Using Deep Learning Techniques, Paperback by Chaki, Jyotismita (EDT), ISBN 0323911714, ISBN-13 9780323911719, Like New Used, Free shipping in the US
<p><i>Brain Tumor MRI Image Segmentation Using Deep Learning Techniques</i> offers a description of deep learning approaches used for the segmentation of brain tumors. Th 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.</p> <p>Th 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. </p><ul> <li>Provides readers with an understanding of deep learning-based approaches in the field of brain tumor segmentation, including preprocessing techniques</li> <li>Integrates recent advancements in the field, including the transformation of low-resolution brain tumor images into super-resolution images using deep learning-based methods, single path Convolutional Neural Network based brain tumor segmentation, and much more</li> <li>Includes coverage of Long Short-Term Memory (LSTM) based Recurrent Neural Network (RNN), Gated Recurrent Units (GRU) based Recurrent Neural Network (RNN), Generative Adversarial Networks (GAN), Auto Encoder based brain tumor segmentation, and Ensemble deep learning Model based brain tumor segmentation</li> <li>Covers research Issues and the future of deep learning-based brain tumor segmentation</li></ul>
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