Magnetic resonance imaging recording, reconstruction and assessment / [electronic resource]:
- 作者： Dey, Nilanjan, 1984-
- 其他作者：
- 其他題名：
- Primers in biomedical imaging devices and systems.
- 出版： London : Academic Press
- 叢書名： Primers in biomedical imaging devices and systems
- 主題： Magnetic resonance imaging. , Magnetic Resonance Imaging , Imagerie par resonance magnetique. , Magnetic resonance imaging.
- ISBN： 9780128234020 (electronic bk.) 、 0128234024 (electronic bk.)
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FIND@SFXID:
CGU
- 資料類型: 電子書
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內容註:
1. Introduction to Image Assisted Disease Screening 2. Magnetic Resonance Imaging -- Recording and Reconstruction 3. Image Processing Schemes to Enhance Disease Information in MRI Slices 4. Segmentation of Tumor in Breast MRI Using Entropy Thresholding and Mayfly-Algorithm: A Study 5. Abnormality Detection in Heart MRI with Spotted-Hyena-Algorithm Supported Kapur/Otsu Thresholding and Level-Set Segmentation 6. CNN based Segmentation of Brain Tumor from T2-Weighted MRI Slices 7. Automated Detection of Ischemic-Stroke with Brain MRI using Machine-Learning and Deep-Learning Features
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讀者標籤：
- 系統號： 005519305 | 機讀編目格式
館藏資訊
Magnetic Resonance Imaging: Recording, Reconstruction and Assessment gives a detailed overview of magnetic resonance imaging (MRI), along with its applications and challenges. The book explores the abnormalities in internal human organs using MRI techniques while also featuring case studies that illustrate measures used. In addition, it explores precautionary measures used during MRI based imaging, the selection of appropriate contrast agents, and the selection of the appropriate modality during the image registration. Sections introduce medical imaging, the use of MRI in brain, cardiac, lung and kidney detection, and also discuss both 2D and 3D imaging techniques and various MRI modalities. This volume will be of interest to researchers, engineers and medical professionals involved in the development and use of MRI systems. - Discusses challenges and issues faced, as well as safety precautions to be followed - Features case studies with benchmark MRIs existing in the literature - Introduces computer-based assessment (Machine Learning and Deep Learning) of the MRI based on its 2D slices