5 papers
Physics-Aware Neural Operators for Direct Inversion in 3D Photoacoustic Tomography
Jiayun Wang, Yousuf Aborahama, Arya Khokhar +10
Learning physics-constrained inverse operators-rather than post-processing physics-based reconstructions-is a broadly applicable strategy for problems with expensive forward models…
Resolution-Agnostic Neural Operators for Multi-Rate Sparse-View CT
Aujasvit Datta, Jiayun Wang, Asad Aali +2
Sparse-view Computed Tomography (CT) reconstructs images from a limited number of X-ray projections to reduce radiation and scanning time, which is an ill-posed inverse problem. Ex…
Coarse Graining with Neural Operators for Simulating Chaotic Systems
Chuwei Wang, Julius Berner, Boris Bonev +6
Accurately predicting the long-term behavior of chaotic systems is crucial for various applications such as climate modeling. However, achieving such predictions typically requires…
A Unified Model for Compressed Sensing MRI Across Undersampling Patterns
Armeet Singh Jatyani, Jiayun Wang, Aditi Chandrashekar +4
Compressed Sensing MRI reconstructs images of the body's internal anatomy from undersampled measurements, thereby reducing scan time. Recently, deep learning has shown great potent…
Ultrasound Lung Aeration Map via Physics-Aware Neural Operators
Jiayun Wang, Oleksii Ostras, Masashi Sode +5
Lung ultrasound is a growing modality in clinics for diagnosing and monitoring acute and chronic lung diseases due to its low cost and accessibility. Lung ultrasound works by emitt…