activity
20202023
most citedRotor Localization and Phase Mapping of Cardiac Excitation Waves using Deep Neural Networks

21 citations · 37 across the 4 of their papers we have counts for

collaborators

5 papers

physics.med-ph2023★ 6 cited

Panoramic Voltage-Sensitive Optical Mapping of Contracting Hearts using Cooperative Multi-View Motion Tracking with 12 to 24 Cameras

Shrey Chowdhary, Jan Lebert, Shai Dickman +2

Voltage-sensitive fluorescence imaging is widely used to image action potential waves in the heart. However, while the electrical waves trigger mechanical contraction, imaging need…

physics.med-ph2023★ 1 cited

Deep Learning-based Prediction of Electrical Arrhythmia Circuits from Cardiac Motion: An In-Silico Study

Jan Lebert, Daniel Deng, Lei Fan +2

The heart's contraction is caused by electrical excitation which propagates through the heart muscle. It was recently shown that the electrical excitation can be computed from the…

q-bio.TO2022★ 9 cited

Reconstruction of Three-dimensional Scroll Waves in Excitable Media from Two-Dimensional Observations using Deep Neural Networks

Jan Lebert, Meenakshi Mittal, Jan Christoph

Scroll wave chaos is thought to underlie life-threatening ventricular fibrillation. However, currently there is no direct way to measure action potential wave patterns transmurally…

physics.med-ph2021★ 21 cited

Rotor Localization and Phase Mapping of Cardiac Excitation Waves using Deep Neural Networks

Jan Lebert, Namita Ravi, Flavio Fenton +1

The analysis of electrical impulse phenomena in cardiac muscle tissue is important for the diagnosis of heart rhythm disorders and other cardiac pathophysiology. Cardiac mapping te…

eess.IV2020

Inverse Mechano-Electrical Reconstruction of Cardiac Excitation Wave Patterns from Mechanical Deformation using Deep Learning

Jan Christoph, Jan Lebert

The inverse mechano-electrical problem in cardiac electrophysiology is the attempt to reconstruct electrical excitation or action potential wave patterns from the heart's mechanica…