- 1:Introduction
- 1.1:Quick review on DTI images
- 1.2:Structure and objective of the book
- 2:Technical review on DTI
- 2.1:Basic principles of diffusion in MRI
- 2.2:Diffusion-weighted imaging
- 2.3:Expanding the representation for the diffusion tensor
- 2.4:References
- 3:DTI analytics and applications
- 3.1:Advantages and limitations of diffusion-weighted imaging
- 3.2:Applications in medicine and research
- 3.3:References
- 4:Computational tools for DTI image analysis
- 4.1:FSL
- 4.1.1:TBSS
- 4.1.2:BEDPOSTX e PROBTRACKX
- 4.2:3D Slicer
- 4.3:MedINRIA
- 4.4:DTI-TK
- 4.4.1:Tract-Specific Analysis (TSA)
- 4.5:References
- 4.1:FSL
- 5:Final thoughts and recommendations for future studies
- 5.1:Key Points to Consider
- 1:Introduction
Diffusion Tensor Imaging Unboxing
A quick guide for beginner researchers
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This guide is designed for researchers who still do not have or have little contact with the diffusion weighted imaging modality (DTI) in MRI. After a few decades of research and development, is now known that the DTI images are extremely powerful for several uses in clinical routine. However, along with these advances of this imaging modality, there are several computational tools for image reconstruction and its visualization. Do not be concerned about what is the first step to understand the DTI imaging modality, because this guide have the intention to summarize the main tools and a brief discussion of what is important to DTI image for modern medicine. See in more detail in the table of contents of this book below or simply download a sample for free.
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Antonio Senra Filho
Antonio Senra Filho has been intensively focused on intelligent systems and how to build machine learning approaches for real-case scenarios. With several known scientific research activities in journals and international conferences, the outcomes reported in the past years helped to achieve a better understanding of practical solutions that can be applied to commercial issues, e.g. document analysis, industry 4.0, smart cities, and so on. Therefore, there is a natural intersection between high-dimensional image analysis, image filtering, multidimensional feature extraction, artificial intelligence, and deep learning algorithms.
Antonio prides himself on sharing his knowledge and experience so feel free to contact him if you have questions, comments or need assistance. LinkedIn and other social network profiles are found by @acsenrafilho.
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