Elizabeth Herbst Email & Phone Number

Cambridge, Massachusetts, United States

Developed deep-learning based solutions for image classification, image segmentation, and computer vision on local and cloud-based platforms, including a machine learning-based super-resolution imaging solution that won 1st Runner Up in the 2022 IEEE International Ultrasonics Symposium.Designed and prototyped advanced image and signal processing techniques to enhance workflow automation, contrast visualization, and super-resolution imaging in medical ultrasound images. Successfully implemented cutting-edge super-resolution imaging techniques to improve visualization of complex vascular networks.Worked with cross-disciplinary teams of clinicians, business leaders, scientists, and developers to translate software imaging features from prototypes to on-cart software features. Acquired feedback from clinicians at each stage of development to deliver meaningful workflow solutions and improve the utility and quality of medical images.

Custom-programmed and implemented ultrasound sequences for a Verasonics Vantage imaging system using MATLAB to produce contrast images of targeted microbubbles. Developed and validated novel statistical signal/image processing and singular value decomposition-based techniques to allow automated real-time visualization of contrast agent binding dynamics in the tumor microvasculature.Implemented strategies to quantify risk assessment in abdominal aortic aneurysms using targeted contrast agents. Coordinating with clinicians, designed an imaging system to apply acoustic radiation force (ARF) to translate microbubbles in the mouse abdominal aorta while simultaneously imaging with a commercial scanner.Key Achievements:- Generated and validated novel image processing algorithms to automatically quantify microbubble binding, culminating in 2 first-author publications in Investigative Radiology and Ultrasound in Medicine and Biology- Communicated research through oral presentations at international ultrasound conferences including International Ultrasonics Symposium, World Molecular Imaging Congress, and won best poster presentation (4 awards given out of 64 presenters) at the European Symposium on Ultrasound Contrast Imaging

415 Lane Road, N. Entrance

Working as a Laboratory Specialist at Hossack Laboratory, I developed and implemented multiple ultrasound pulse sequences (pulse inversion, CPS) on a Verasonics system for contrast imaging.

Mountain View, Ca

As an intern at Siemens Healthineers, I developed methods to eliminate signals from grating lobe artifacts using both AI-based and algorithmic techniques.Key Achievements:- Programmed a GUI in MATLAB to annotate 3,000 cardiac ultrasound DICOM images and configured SegNet, a convolutional neural network, to reduce grating lobe artifacts in augmented image data sets.- Implemented a patented adaptive filtering technique to reduce grating lobe artifact signals in cardiac ultrasound images.- Presented a technical overview of neural network theory and architecture to 2 teams of engineers, finance officers and managers.

Phd, Biomedical Engineering, School Of Engineering And Applied Science, Diagnostic Ultrasound

Bachelor Of Science (B.S.), Biomedical Engineering, School Of Engineering And Applied Science, 3.57

Activities and Societies: Society of Women Engineers (SWE), Institute of Electrical and Electronics Engineers (IEEE), Alpha Phi Omega.