基本信息
views: 7
Career Trajectory
Bio
Education & Training
Neuroradiology Fellowship
UCSF (2017)
Diagnostic Radiology Residency
University of Minnesota (2016)
Transitional Year Internship
Hennepin County Medical Center (2012)
Research Fellow
Massachusetts General Hospital (2011)
MD
Tehran University (2007)
Research Summary
Most of my research has been focused on application of advanced imaging techniques and development of novel neuroimaging-based models for outcome prediction and treatment triage in stroke patients. However, the scope of my research projects have been expanded to apply radiomics, bioimage texture analysis, machine learning classifiers, and deep learning for development of innovative neuroimaging diagnostic tools. Many of these tools have been successfully helped with prognostication of cerebrovascular disease, identification of children with neurodevelopmental disorders, and differentiation of brain and neck tumors. The mainstay of projects is to combine advanced neuroimaging statistics, machine learning models, and outcome research to devise cutting-edge predictive tools, and provide personalized treatment options for patients.
Extensive Research Description
Stroke imaging: Devising prognostic model for stroke patients based on the location of brain parenchymal damage on initial scans. Application of deep neural networks for identification of acute infarct on head CT, localization of arterial occlusion, and grading of arterial collaterals on admission CT angiography. Outcome prediction based on imaging patterns of hemorrhagic stroke.
Head and neck cancers: Applying texture analysis, radiomics and machine-learning models for differentiation of neoplasms, prediction of molecular subtypes, and prognostication beyond current staging schemes based on CT, MRI, and PET scans in patients with tumors of brain and neck.
Brain connectivity in neurodevelopmental disorders: Examining the functional and microstructural connectivity of the brain in children at risk of autism and neurodevelopmental disorders based on diffusion tensor imaging and tractography. Using machine learning models to devise bioimaging biomarkers for neurodevelopmental disease based on quantitative metrics of brain connectivity.
Research Interests
Artificial Intelligence; Brain Diseases; Brain Neoplasms; Neurology; Neurosciences; Neurosurgery; Brain Hemorrhage, Traumatic; Stroke; Diffusion Magnetic Resonance Imaging; Neuroimaging; Autism Spectrum Disorder; Machine Learning; Neurodevelopmental Disorders
Neuroradiology Fellowship
UCSF (2017)
Diagnostic Radiology Residency
University of Minnesota (2016)
Transitional Year Internship
Hennepin County Medical Center (2012)
Research Fellow
Massachusetts General Hospital (2011)
MD
Tehran University (2007)
Research Summary
Most of my research has been focused on application of advanced imaging techniques and development of novel neuroimaging-based models for outcome prediction and treatment triage in stroke patients. However, the scope of my research projects have been expanded to apply radiomics, bioimage texture analysis, machine learning classifiers, and deep learning for development of innovative neuroimaging diagnostic tools. Many of these tools have been successfully helped with prognostication of cerebrovascular disease, identification of children with neurodevelopmental disorders, and differentiation of brain and neck tumors. The mainstay of projects is to combine advanced neuroimaging statistics, machine learning models, and outcome research to devise cutting-edge predictive tools, and provide personalized treatment options for patients.
Extensive Research Description
Stroke imaging: Devising prognostic model for stroke patients based on the location of brain parenchymal damage on initial scans. Application of deep neural networks for identification of acute infarct on head CT, localization of arterial occlusion, and grading of arterial collaterals on admission CT angiography. Outcome prediction based on imaging patterns of hemorrhagic stroke.
Head and neck cancers: Applying texture analysis, radiomics and machine-learning models for differentiation of neoplasms, prediction of molecular subtypes, and prognostication beyond current staging schemes based on CT, MRI, and PET scans in patients with tumors of brain and neck.
Brain connectivity in neurodevelopmental disorders: Examining the functional and microstructural connectivity of the brain in children at risk of autism and neurodevelopmental disorders based on diffusion tensor imaging and tractography. Using machine learning models to devise bioimaging biomarkers for neurodevelopmental disease based on quantitative metrics of brain connectivity.
Research Interests
Artificial Intelligence; Brain Diseases; Brain Neoplasms; Neurology; Neurosciences; Neurosurgery; Brain Hemorrhage, Traumatic; Stroke; Diffusion Magnetic Resonance Imaging; Neuroimaging; Autism Spectrum Disorder; Machine Learning; Neurodevelopmental Disorders
Research Interests
Papers共 180 篇Author StatisticsCo-AuthorSimilar Experts
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Julia Zabinska,Vineetha Yadlapalli,Mercy Mazurek,Nethra Parasuram, Dheeraj Lalwani, Emma Peasley,Emily Gilmore,Jennifer Kim,Sacit Bulent Omay,Gordon Sze,Sam Payabvash,Annabel Sorby-Adams,
Emily W. Avery, Anthony Abou-Karam, Sandra Abi-Fadel,Jonas Behland,Adrian Mak,Stefan P. Haider,Tal Zeevi,Pina C. Sanelli,Christopher G. Filippi,Ajay Malhotra,Charles C. Matouk,Guido J. Falcone,
DIAGNOSTICSno. 5 (2024): 485
Ajay Malhotra, Dheeman Futela,Mihir Khunte, Shadi Ebrahimian, Chris Lee,Xiao Wu,Seyedmehdi Payabvash,Dheeraj Gandhi
Academic Radiology (2024)
Gaby Abou Karam, Min-Chiun Chen, Dorin Zeevi, Bendix C. Harms,Victor M. Torres-Lopez,Cyprien A. Rivier,Ajay Malhotra,Adam de Havenon,Guido J. Falcone,Kevin N. Sheth,Seyedmehdi Payabvash
DIAGNOSTICSno. 3 (2024): 308
Journal of nuclear medicine : official publication, Society of Nuclear Medicineno. 5 (2024): 803-809
Neuroimaging clinics of North Americano. 1 (2024): 167-173
Journal of the American College of Radiology (2024)
Dheeman Futela,Suryansh Bajaj,Mihir Khunte,Xiao Wu,Seyedmehdi Payabvash,Dheeraj Gandhi,Ajay Malhotra
CLINICAL IMAGING (2024): 109995-109995
Ajay Malhotra, Dheeman Futela,Mihir Khunte, Nagaraj S. Moily,Xiao Wu,Seyedmehdi Payabvash,Dheeraj Gandhi
The American Journal of the Medical Sciences (2024)
Anh T. Tran,Tal Zeevi,Stefan P. Haider, Gaby Abou Karam,Elisa R. Berson,Hishan Tharmaseelan, Adnan I. Qureshi,Pina C. Sanelli,David J. Werring,Ajay Malhotra,Nils H. Petersen,Adam de Havenon,
npj Digital Medicineno. 1 (2024): 1-11
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