Simulation and Data Lab Neuroscience
Major Competencies
With a core expertise in 3D medical image analysis of the human brain, the lab combines advanced engineering techniques to offer detailed insights into brain anatomy. The research is centered on automated segmentation of brain structures, with a particular emphasis on understanding the intricacies of aging brains and the manifestations of conditions such as Alzheimer's. Concurrently, efforts are made to bridge the domains of medical imaging and genetics, especially concerning brain structural variations in children with genetic syndromes
Advanced Medical Imaging and Neurological Analysis
Expertise in cutting-edge medical image processing and interpretation, with a strong emphasis on analyzing brain features and structures. Specialization extends to the segmentation of various anatomical components, delving deep into the intricacies of aging brains and conditions such as Alzheimer's and mild cognitive impairment
Deep Learning and AI in Medical Imaging
Recognized for the systematic application of artificial intelligence techniques in medical imaging tasks. The emphasis is on the utilization of deep learning algorithms for image enhancement, lesion detection, and anatomical feature segmentation, contributing to more precise and detailed image interpretations
Scalable Data Processing and Integration:
Showcasing consistent proficiency in handling vast datasets through scalable data processing, analytics, and the integration of standards-based architectures. This approach ensures efficient data management, merging high-throughput data analysis with advanced computational methods
Lab news and events
People
Dr. Lotta María Ellingsen
Lotta holds a BS in Electrical and Computer Engineering from the University of Iceland (2001), an MSE (2004), and a Ph.D. (2008) from Johns Hopkins University in the same field. She further enriched her expertise as a Post-doctoral Fellow at Johns Hopkins University from 2009 to 2010. Lotta has applied engineering methods to medicine, emphasizing three-dimensional medical image registration and segmentation. She specializes in deformable 3D-3D image registration of the human brain and has developed pipelines for automatic segmentation and labeling of brain anatomy. Her recent work aims to characterize clinical syndromes in elderly patients and integrate medical image analysis with genetics to study brain structural abnormalities in children.