{Seminar} @ CDS: #102 : 30th August: “Recon-all-clinical Cortical analysis of heterogeneous clinical brain MRI scans”


30 Aug 23    
11:00 AM - 12:00 PM

Event Type

Department of Computational and Data Sciences
Department Seminar

SPEAKER : Karthik Gopinath is a Postdoctoral Research Fellow at Athinoula A.

TITLE : “Recon-all-clinical Cortical analysis of heterogeneous clinical brain MRI scans“

Date & Time : August 30, 2023, 11:00 AM

Venue : # 102, CDS Seminar Hall



Surface analysis of the cortex is ubiquitous in human neuroimaging with MRI, e.g., for cortical registration, parcellation, or thickness estimation. The convoluted cortical geometry requires isotropic scans (e.g., 1mm MPRAGEs) and good gray-white matter contrast for 3D reconstruction. This precludes the analysis of most brain MRI scans ac- quired for clinical purposes. Analyzing such scans would enable neuroimaging studies with sample sizes that cannot be achieved with current research datasets, particularly for underrepresented populations and rare diseases. Here we present the first method for cortical reconstruction, registration, parcellation, and thickness estimation for clinical brain MRI scans of any resolution and pulse sequence. The methods have a learning component and a classical optimization module. The former uses domain randomization to train a CNN that predicts an implicit representation of the white matter and pial surfaces (a signed distance function) at 1mm isotropic resolution, independently of the pulse sequence and resolution of the input. The latter uses geometry processing to place the surfaces while accurately satisfying topological and geometric constraints, thus enabling subsequent parcellation and thickness estimation with existing methods. We present results on 5mm axial FLAIR scans from ADNI and on a highly heterogeneous clinical dataset with 5,000 scans.


Karthik Gopinath is a Postdoctoral Research Fellow at Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, and Harvard Medical School. His work focuses on Brain surface analysis of clinically acquired MR images. Previously he completed his Ph.D. from ETS Montreal, where his work focused on Geometric learning for brain surface analysis, for which he received the Governor-general academic gold medal and Best Thesis award. He completed his MS by Research from IIIT-Hyderabad. You can find more information about his work on his webpage: https://sites.google.com/site/karthikharitz/

Host Faculty: Dr. Vaanathi Sundaresan