Ken D. Sauer — accepted AI-conference papers

2021

A Bias-Reducing Loss Function for CT Image Denoising

Madhuri Nagare, Roman Melnyk, Obaidullah Rahman, Ken D. Sauer, Charles A. Bouman

ICASSP 2021accepted

There is growing interest in the use of deep neural network (DNN) based image denoising to reduce patient’s X-ray dosage in medical computed tomography (CT). An effective denoiser must remove noise while maintaining the texture and detail. Commonly used mean squared error (MSE) loss functions in the…

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2018

Deep Residual Learning for Model-Based Iterative CT Reconstruction Using Plug-and-Play Framework

Dong Hye Ye, Somesh Srivastava, Jean-Baptiste Thibault, Ken D. Sauer, Charles A. Bouman

ICASSP 2018accepted

Model-Based Iterative Reconstruction (MBIR) has shown promising results in clinical studies as they allow significant dose reduction during CT scans while maintaining the diagnostic image quality. MBIR improves the image quality over analytical reconstruction by modeling both the sensor (e.g., forwa…

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