Idan Steinberg
Senior Director Of Research & Development Vice President, Research & Development at ENDRA Life Sciences (Nasdaq: NDRA)
Ann Arbor, Michigan, United States
Summary
👤
Senior🎓
Top SchoolIdan Steinberg is a versatile R&D leader with nearly two decades of experience translating biomedical optics and acoustic imaging research into clinical-grade devices and trials. Currently VP of Research and Development at ENDRA Life Sciences, he has led multidisciplinary teams to deliver complex photoacoustic, RF-acoustic, and molecular imaging systems from concept through pilot clinical studies. His background spans hands-on algorithm and system development—from SVM classifiers for rapid bacterial ID to real-time software for animal virtual tactile experiments—and includes multiple fellowships and successful tech translations at Stanford. Known as a personable consensus-builder, he pairs technical depth in signal processing and device engineering with regulatory and product strategy. He also brings business acumen through executive training at the University of Michigan, and an ability to pivot between academic rigor and startup speed. An underappreciated strength is his track record of embedding practical data analysis into program decisions to de-risk translation and accelerate clinical impact.
9 years of coding experience
1 year of employment as a software developer
Ph.D Biomedical Engineering, Ph.D Biomedical Engineering at Tel Aviv UniversityAccelerated Management Development Certificate Program (AMDCP) Business Administration and Management, Accelerated Management Development Certificate Program (AMDCP) Business Administration and Management at University of Michigan - Stephen M. Ross School of Business
English, Hebrew
Github Skills (4)
image-reconstruction7
imaging6
algorithm5
algorithms4
Programming languages (1)
Github contributions (4)
idanstei/Superiorized-Photo-Acoustic-Non-NEgative-Reconstruction-for-Clinical-Photoacoustic-Imaging
Oct 2020 - Apr 2021
Photoacoustic (PA) imaging can revolutionize medical ultrasound by augmenting it with molecular information. However, clinical translation of PA imaging remains a challenge due to the limited viewing angles and imaging depth. Described here is a new robust algorithm called Superiorized Photo-Acoustic Non-NEgative Reconstruction (SPANNER), designed to reconstruct PA images in real-time and to address these limitations. The method utilizes precise forward modeling of the PA propagation and reception of signals while accounting for the effects of acoustic absorption, element size, shape, and sensitivity, as well as the transducer's impulse response and directivity pattern. A fast superiorized conjugate gradient algorithm is used for inversion. SPANNER is compared to three reconstruction algorithms: delay-and-sum (DAS), universal back-projection (UBP), and model-based reconstruction (MBR). All four algorithms are applied to both simulations and experimental data acquired from tissue-mimicking phantoms, ex vivo tissue samples, and in vivo imaging of the prostates in patients. Simulations and phantom experiments highlight the ability of SPANNER to improve contrast to background ratio by up to 20 dB compared to all other algorithms, as well as a 3-fold increase in axial resolution compared to DAS and UBP. Applying SPANNER on contrast-enhanced PA images acquired from prostate cancer patients yielded a statistically significant difference before and after contrast agent administration, while the other three image reconstruction methods did not, thus highlighting SPANNER's performance in differentiating intrinsic from extrinsic PA signals and its ability to quantify PA signals from the contrast agent more accurately.
Contributions:4 commits, 1 push in 5 months
image-reconstructionimaging
Contributions:3 pushes, 1 branch in 9 days
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