Dhineshvikram Krishnamurthy, MS

Software Engineer

Dhineshvikram Krishnamurthy, MS, is a software engineer whose expertise is developing the integrated research information system for fetal and neonatal MRI data management, processing and visualization to better inform clinicians’ diagnoses.

Address: 111 Michigan Ave NW, Washington, DC 20010
Email: fetalbrain@childrensnational.org
Department: MRI Lab

Recent Publications & Presentations

De Asis-Cruz J, Krishnamurthy D, Zhao L, Kapse K, Vezina G, Andescavage N, Quistorff J, Lopez C, Limperopoulos C.
Association of prenatal maternal anxiety with fetal regional brain connectivity JAMA Network Open. Published 2020, Dec. 7;3(12):e2022349. doi:10.1001/jamanetworkopen.2020.22349 https://pubmed.ncbi.nlm.nih.gov/33284334/
Krishnamurthy D, Wu Y, Largent A, Kapse K, Amgalan A, Andescavage N, Zhao L, Limperopoulos C.
Automated fetal whole-body MRI segmentation using a 3D U-Net Deep Learning Method.
Conference: Pediatric Academic Societies, 2020.
Krishnamurthy D, You W, Kapse K, Limperopoulos C.
Real-time ultrafast fetal brain localization using convolutional neural networks.
Conference: ISMRM 27th Annual Meeting & Exhibition, 2019 [Poster]
Krishnamurthy D, Kim S, Scalise B, Kapse K, You W, Limperopoulos C.
Integrated Research Information System (IRIS) - Real-time multi-platform fetal and neonatal brain MRI processing and visualization toolkit.
Conference: International Symposium on the Fetal Brain, 2018
You W, Kapse K, Wu Y, Krishnamurthy D, Limperopoulos C.
Automatic segmentation of the fetal brain using multi-scale 3D convolutional neural network: A pilot study.
Conference: ISMRM Workshop on Machine Learning, Part II, 2018 [Poster]