Brain Tumor MRI Image Segmentation Using Deep Learning Techniques

The book "Brain Tumor MRI Image Segmentation Using Deep Learning Techniques" demonstrates how deep learning approaches can be used for brain tumor segmentation. It covers techniques for modeling, segmentation, and properties, and highlights the application of convolutional neural networks to address new questions and protocols.

Format: Paperback / softback
Length: 258 pages
Publication date: 02 December 2021
Publisher: Elsevier Science & Technology

Brain Tumor MRI Image Segmentation Using Deep Learning Techniques is a comprehensive guide that delves into the utilization of deep learning techniques for the segmentation of brain tumors. The book presents core concepts of deep learning algorithms through the use of diagrams, data tables, and illustrative examples, effectively demonstrating the process of brain tumor segmentation. Following an introductory overview of deep learning-based brain tumor segmentation, subsequent sections explore various techniques for modeling, segmentation, and properties. A significant emphasis is placed on the application of diverse convolutional neural networks, including single path, multi path, fully convolutional network, cascade convolutional neural networks, Long Short-Term Memory - Recurrent Neural Network, and Gated Recurrent Units, among others. Furthermore, the book underscores how the integration of deep neural networks can address novel questions and protocols, as well as enhance existing challenges in brain tumor segmentation.

Weight: 542g
Dimension: 234 x 191 x 20 (mm)
ISBN-13: 9780323911719