The past 20 years have seen a mushrooming growth of the field of computational neuroanatomy. Much of this work has been enabled by the development and refinement of powerful, high-dimensional image warping methods, which have enabled detailed brain p...
BACKGROUND: Current computational neuroanatomy focuses on morphological measurements of the brain using standard magnetic resonance imaging (MRI) techniques. In comparison quantitative MRI (qMRI) typically provides a better tissue contrast and also g...
Whole brain segmentation from structural magnetic resonance imaging (MRI) is a prerequisite for most morphological analyses, but is computationally intense and can therefore delay the availability of image markers after scan acquisition. We introduce...
Autism spectrum disorder (ASD) is highly heterogeneous. Identifying systematic individual differences in neuroanatomy could inform diagnosis and personalized interventions. The challenge is that these differences are entangled with variation because ...
BACKGROUND: The complexity of the relationships among the structures within the brain makes efficient mastery of neuroanatomy difficult for medical students and neurosurgical residents. Therefore, there is a need to provide real-time segmentation of ...
We tested to see how Ruben's copy of "The Battle of Anghiari" by Leonardo da Vinci would be interpreted by AI in a neuroanatomical aspect. We used WOMBO Dream, an artificial intelligence (AI)-based algorithm that creates images based on words and fig...
Dr. Deepak "Dee" Pandya spent his career as an internal medicine physician as well as in his respective laboratories at the Bedford, Massachusetts Veterans Administration Hospital and at Boston University School of Medicine. His achievements mapping ...
BACKGROUND: The skull base is a complex region in neurosurgery, featuring numerous foramina. Accurate identification of these foramina is imperative to avoid intraoperative complications and to facilitate educational progress in neurosurgical trainee...