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Found 7 papers, 2 papers with code
EAGLE: An Edge-Aware Gradient Localization Enhanced Loss for CT Image Reconstruction
However, the choice of loss function profoundly affects the reconstructed images.
Data-Driven Filter Design in FBP: Transforming CT Reconstruction with Trainable Fourier Series
In this study, we introduce a Fourier series-based trainable filter for computed tomography (CT) reconstruction within the filtered backprojection (FBP) framework.
Attention-Guided Erasing: A Novel Augmentation Method for Enhancing Downstream Breast Density Classification
The assessment of breast density is crucial in the context of breast cancer screening, especially in populations with a higher percentage of dense breast tissues.
Heat Demand Forecasting with Multi-Resolutional Representation of Heterogeneous Temporal Ensemble
A minimal mean error of 7. 54% for MAPE and 417kW for RMSE is achieved with the proposed framework in comparison to all other methods.
Prediction of Household-level Heat-Consumption using PSO enhanced SVR Model
In combating climate change, an effective demand-based energy supply operation of the district energy system (DES) for heating or cooling is indispensable.
An Investigation of Feature-based Nonrigid Image Registration using Gaussian Process
For a wide range of clinical applications, such as adaptive treatment planning or intraoperative image update, feature-based deformable registration (FDR) approaches are widely employed because of their simplicity and low computational complexity.
Analyzing an Imitation Learning Network for Fundus Image Registration Using a Divide-and-Conquer Approach
In this work, we propose an imitation learning framework for the registration of 2D color funduscopic images for a wide range of applications such as disease monitoring, image stitching and super-resolution.
