Biography

Bio & Research

Dr. Brattain holds a PhD in engineering sciences from Harvard John A. Paulson School of Engineering and Applied Sciences. Her doctoral research focused on ultrasound-guided surgical robots for minimally invasive beating-heart procedures.

Dr. Brattain’s research integrates biomedical artificial intelligence (AI), medical ultrasound, and surgical robotics. She has a proven track record in fostering collaborations, leading multidisciplinary teams, mentoring students and early-career researchers, and facilitating translational AI applications. Her focus in AI research revolves around the dynamic integration of real-time capabilities, extending from cloud computing to lightweight edge AI on smart devices. Driven by a passion for healthcare innovation, she directs her expertise towards the development of real-time diagnostic assistants and advancements in minimally invasive procedures. These endeavors are geared towards enhancing clinical decision support and empowering medical professionals with intelligent medical care capabilities in diverse clinical settings.

Dr. Brattain is an Associated Professor of Medicine in the Dept. of Internal Medicine. She also holds secondary positions in the Dept. of Electrical and Computer Engineering and Dept. of Computer Science in the College of Engineering.

Dr. Brattain is an IEEE Senior Member, a member of the IEEE Engineering in Medicine and Biology Society, and a member of IEEE Women in Engineering. She currently serves as a co-chair of the American Institute of Ultrasound for Medicine (AIUM) AI Community.

Education and Specialties

PhD, Engineering Sciences, Harvard John A. Paulson School of Engineering and Applied Sciences, Cambridge, MA

Biomedical AI

Clinical decision support

High performance computing

Medical ultrasound

Medical devices

Surgical robotics

Selected Publications

Shamsi, N.I., Xu, A.S., Gjesteby, L.A. & Brattain, L.J., 2024. Improved Topological Preservation in 3D Axon Segmentation and Centerline Detection using Geometric Assessment-driven Topological Smoothing (GATS). In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (pp. 8005-8014).

Book Chapter: Gjesteby, L. A., Pare, J. R., & Brattain, L. J. (2022). Ultrasound for the Emergency Department and Prehospital Care. In Engineering and Medicine in Extreme Environments (pp. 209-234). Cham: Springer International Publishing.

Book Chapter: Telfer, B. A., Kumar, V., Aguirre, A. D., Samir, A. E., & Brattain, L. J. (2021). Ultrasound and artificial intelligence. In Machine Learning in Cardiovascular Medicine (pp. 177-210). Academic Press.

Pare, J. R., Gjesteby, L. A., Telfer, B. A., Tonelli, M. M., Leo, M. M., Billatos, E., … & Brattain, L. J. (2022, July). Transfer Learning for Automated COVID-19 B-Line Classification in Lung Ultrasound. In 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) (pp. 1675-1681). IEEE.

Brattain, L.J., Pierce, T.T., Gjesteby, L.A., Johnson, M.R., DeLosa, N.D., Werblin, J.S., Gupta, J.F., Ozturk, A., Wang, X., Li, Q. and Telfer, B.A., 2021. AI-Enabled, Ultrasound-Guided Handheld Robotic Device for Femoral Vascular Access. Biosensors, 11(12), p.522.

Brattain, L.J., Ozturk, A., Telfer, B.A., Dhyani, M., Grajo, J.R. and Samir, A.E., 2020. Image processing pipeline for liver fibrosis classification using ultrasound shear wave elastography. Ultrasound in medicine & biology, 46(10), pp.2667-2676.

Klinghoffer, T., Morales, P., Park, Y. G., Evans, N., Chung, K., & Brattain, L. J. (2020). Self-supervised feature extraction for 3D axon segmentation. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (pp. 978-979).

Brattain, L.J., Telfer, B.A., Dhyani, M., Grajo, J.R. and Samir, A.E., 2018. Machine learning for medical ultrasound: status, methods, and future opportunities. Abdominal Radiology, 43(4), pp.786-799.

Brattain, L.J., Samir, A.E., Telfer, B.A., Johnson, M., DeLosa, N., Gjesteby, L., Pierce, T.T. and Werblin, J., General Hospital Corp and Massachusetts Institute of Technology, 2023. Systems and methods for guided intervention. U.S. Patent Application 17/971,073.

Brattain, L.J., Samir, A.E., Telfer, B.A., DeLosa, N., Gjesteby, L., Pierce, T.T., Johnson, M., Hill, W. and Chamorro, A., Massachusetts Institute of Technology, 2021. Systems and methods for portable ultrasound guided cannulation. U.S. Patent Application 16/995,637.

Brattain, L., Dhyani, M., Samir, A.E. and Telfer, B.A., General Hospital Corp and Massachusetts Institute of Technology, 2021. Method for objective, noninvasive staging of diffuse liver disease from ultrasound shear-wave elastography. U.S. Patent Application 17/040,473.