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Computational neuroanatomy is about a comprehensive structural and functional model of the brain. The distribution of structural changes of human brain reflects the underlying pathology. The increasing sophistication of MRI allows neuroanatomical structures to be visualized in vivo in unprecedented detail. Clinical MRI is able to give good soft-tissue contrast and high spatial (<1 mm) resolution. Due to rapid advances in computing power and algorithm development, we are now well placed to study the extraordinary MRI-visible morphological variability of the human brain through mathematical models sensitive to subtle changes in neuroanatomical shape, complexity and tissue characteristics. One of the key requirements of neuroimaging research is the multi-disciplinary collaborations between neuroscience, engineering and medicine and a host of sub-disciplines. While the research subjects and the clinical needs are provided by medicine, the theoretical underpinnings come from mathematics and statistics, and the methodological approaches from computer science and biomedical engineering, all forming critical components of the enterprise. Our recent work includes mapping and modeling of cerebral white matter hyperintensities, algorithm development for examining the shapes and sizes of brain structures and cortical atrophy. fMRI, pMRI, MRS, and PET are also currently being used as brain imaging modalities in various studies.
Computational neuroanatomy is about a comprehensive structural and functional model of the brain. The distribution of structural changes of human brain reflects the underlying pathology. The increasing sophistication of MRI allows neuroanatomical structures to be visualized in vivo in unprecedented detail. Clinical MRI is able to give good soft-tissue contrast and high spatial (<1 mm) resolution. Due to rapid advances in computing power and algorithm development, we are now well placed to study the extraordinary MRI-visible morphological variability of the human brain through mathematical models sensitive to subtle changes in neuroanatomical shape, complexity and tissue characteristics. One of the key requirements of neuroimaging research is the multi-disciplinary collaborations between neuroscience, engineering and medicine and a host of sub-disciplines. While the research subjects and the clinical needs are provided by medicine, the theoretical underpinnings come from mathematics and statistics, and the methodological approaches from computer science and biomedical engineering, all forming critical components of the enterprise. Our recent work includes mapping and modeling of cerebral white matter hyperintensities, algorithm development for examining the shapes and sizes of brain structures and cortical atrophy. fMRI, pMRI, MRS, and PET are also currently being used as brain imaging modalities in various studies.
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ALZHEIMER'S & DEMENTIA: DIAGNOSIS, ASSESSMENT & DISEASE MONITORINGno. 1 (2024): e12567-e12567
Jing Du,Yuangang Pan,Jiyang Jiang,Ben C. P. Lam, Anbupalam Thalamuthu,Rory Chen,Ivor W. Tsang,Perminder S. Sachdev,Wei Wen
European Archives of Psychiatry and Clinical Neurosciencepp.1-11, (2024)
Frontiers in oncology (2024): 1277206-1277206
Brain Structure and Functionpp.1-13, (2024)
JTCVS TECHNIQUES (2024): 104-108
Jing Du, Yuangang Pan,Jiyang Jiang,Yue Liu,Ben C P Lam,Aletta E Schutte, Ivor W Tsang,Perminder S Sachdev,Wei Wen
Hypertension (Dallas, Tex. : 1979)no. 4 (2024): 906-916
Marina Ulanova,Lucy Gloag,Andre Bongers, Chul-Kyu Kim, Hong Thien Kim Duong,Ha Na Kim,John Justin Gooding,Richard D. Tilley,Joanna Biazik,Wei Wen,Perminder S. Sachdev,Nady Braidy,
medRxiv (Cold Spring Harbor Laboratory) (2023)
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