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Found 5 papers, 4 papers with code
Towards Real-time Training of Physics-informed Neural Networks: Applications in Ultrafast Ultrasound Blood Flow Imaging
In this article, we first propose a novel training framework of PINN for solving Navier-Stokes equations by discretizing Navier-Stokes equations into steady state and sequentially solving steady-state Navier-Stokes equations with transfer learning.
Constrained CycleGAN for Effective Generation of Ultrasound Sector Images of Improved Spatial Resolution
In vitro phantom results demonstrate that CCycleGAN successfully generates images with improved spatial resolution as well as higher peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) compared with benchmarks.
Exploring Concept Contribution Spatially: Hidden Layer Interpretation with Spatial Activation Concept Vector
To tackle this problem, based on TCAV, we propose Spatial Activation Concept Vector (SACV) which identifies the relevant spatial locations to the query concept while evaluating their contributions to the model prediction of the target class.
HINT: Hierarchical Neuron Concept Explainer
To this end, we propose HIerarchical Neuron concepT explainer (HINT) to effectively build bidirectional associations between neurons and hierarchical concepts in a low-cost and scalable manner.
NaviAirway: a Bronchiole-sensitive Deep Learning-based Airway Segmentation Pipeline
Airway segmentation is essential for chest CT image analysis.
