Automated Brain Extraction in MRI
Techniques and Applications in T1-Weighted Coronal Imaging
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Magnetic Resonance Imaging (MRI) is a vital tool in diagnosing and planning treatment for neurological disorders, offering detailed views of brain structures. Yet, traditional manual interpretation is time-consuming and prone to variability. This book presents six novel automated brain extraction (skull stripping) methods developed from my doctoral research to improve accuracy, efficiency, and consistency in MRI brain tissue segmentation. Using advanced computational techniques such as fuzzy logic, Helmholtz free energy, bond number, block truncation coding, morphological operations, grayscale...
Magnetic Resonance Imaging (MRI) is a vital tool in diagnosing and planning treatment for neurological disorders, offering detailed views of brain structures. Yet, traditional manual interpretation is time-consuming and prone to variability. This book presents six novel automated brain extraction (skull stripping) methods developed from my doctoral research to improve accuracy, efficiency, and consistency in MRI brain tissue segmentation. Using advanced computational techniques such as fuzzy logic, Helmholtz free energy, bond number, block truncation coding, morphological operations, grayscale transformation, and a modified distance transform, these methods are rigorously compared with established tools like BET and BSE. The work bridges brain anatomy, MRI principles, and digital image processing, culminating in performance evaluations and future research insights. Supported by collaborations with medical experts, academic guidance, and contributions from MRI dataset providers, this book offers researchers, students, and practitioners in medical image processing and neuroimaging a valuable and practical reference.
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