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02/08/2022
Trained Model in Supervised Deep Learning is a Conditional Risk Minimizer
We proved that a trained model in supervised deep learning minimizes the...
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09/26/2020
Deep Learning-based Four-region Lung Segmentation in Chest Radiography for COVID-19 Diagnosis
Purpose. Imaging plays an important role in assessing severity of COVID ...
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06/03/2020
Learning to Scan: A Deep Reinforcement Learning Approach for Personalized Scanning in CT Imaging
Computed Tomography (CT) takes X-ray measurements on the subjects to rec...
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05/22/2020
Deep Learning Based Detection and Localization of Cerebal Aneurysms in Computed Tomography Angiography
Detecting cerebral aneurysms is an important clinical task of brain comp...
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05/19/2020
Self-supervised Dynamic CT Perfusion Image Denoising with Deep Neural Networks
Dynamic computed tomography perfusion (CTP) imaging is a promising appro...
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06/09/2019
Consensus Neural Network for Medical Imaging Denoising with Only Noisy Training Samples
Deep neural networks have been proved efficient for medical image denois...
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10/05/2018
Computationally Efficient Cascaded Training for Deep Unrolled Network in CT Imaging
Dose reduction in computed tomography (CT) has been of great research in...
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11/06/2017
End-to-End Abnormality Detection in Medical Imaging
Nearly all of the deep learning based image analysis methods work on rec...
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05/11/2017