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08/24/2023
DeepLOC: Deep Learning-based Bone Pathology Localization and Classification in Wrist X-ray Images
In recent years, computer-aided diagnosis systems have shown great poten...
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11/01/2022
Self-supervised Physics-based Denoising for Computed Tomography
Computed Tomography (CT) imposes risk on the patients due to its inheren...
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09/28/2022
Medical Image Captioning via Generative Pretrained Transformers
The automatic clinical caption generation problem is referred to as prop...
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08/31/2022
PyTorch Image Quality: Metrics for Image Quality Assessment
Image Quality Assessment (IQA) metrics are widely used to quantitatively...
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07/31/2022
Feather-Light Fourier Domain Adaptation in Magnetic Resonance Imaging
Generalizability of deep learning models may be severely affected by the...
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03/15/2022
Image Quality Assessment for Magnetic Resonance Imaging
Image quality assessment (IQA) algorithms aim to reproduce the human's p...
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03/10/2022
Autofocusing+: Noise-Resilient Motion Correction in Magnetic Resonance Imaging
Image corruption by motion artifacts is an ingrained problem in Magnetic...
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08/29/2021
Decentralized Autofocusing System with Hierarchical Agents
State-of-the-art object detection models are frequently trained offline ...
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08/10/2021
Optimal MRI Undersampling Patterns for Ultimate Benefit of Medical Vision Tasks
To accelerate MRI, the field of compressed sensing is traditionally conc...
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06/10/2021
Strong Gaussian Approximation for the Sum of Random Vectors
This paper derives a new strong Gaussian approximation bound for the sum...
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04/02/2021
Data Augmentation with Manifold Barycenters
The training of Generative Adversarial Networks (GANs) requires a large ...
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03/04/2021
Towards Ultrafast MRI via Extreme k-Space Undersampling and Superresolution
We went below the MRI acceleration factors (a.k.a., k-space undersamplin...
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02/03/2021
No-reference denoising of low-dose CT projections
Low-dose computed tomography (LDCT) became a clear trend in radiology wi...
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01/20/2021
Active Learning for Sequence Tagging with Deep Pre-trained Models and Bayesian Uncertainty Estimates
Annotating training data for sequence tagging tasks is usually very time...
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10/02/2020
Adaptive Neural Layer for Globally Filtered Segmentation
This study is motivated by typical images taken during ultrasonic examin...
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10/02/2020
Tubular Shape Aware Data Generation for Semantic Segmentation in Medical Imaging
Chest X-ray is one of the most widespread examinations of the human body...
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07/09/2020
Learnable Hollow Kernels for Anatomical Segmentation
Segmentation of certain hollow organs, such as the bladder, is especiall...
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06/23/2020
Anomaly Detection with Deep Perceptual Autoencoders
Anomaly detection is the problem of recognizing abnormal inputs based on...
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06/22/2020
Deep Negative Volume Segmentation
Clinical examination of three-dimensional image data of compound anatomi...
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06/20/2020
BRULÉ: Barycenter-Regularized Unsupervised Landmark Extraction
Unsupervised retrieval of image features is vital for many computer visi...
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02/22/2020
Reinforcement Learning Framework for Deep Brain Stimulation Study
Malfunctioning neurons in the brain sometimes operate synchronously, rep...
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02/07/2020
Unsupervised non-parametric change point detection in quasi-periodic signals
We propose a new unsupervised and non-parametric method to detect change...
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11/25/2019
