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Anatomy-guided Multimodal Registration by Learning Segmentation without Ground Truth: Application to Intraprocedural CBCT/MR Liver Segmentation and Registration
Multimodal image registration has many applications in diagnostic medica...
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Conditional Training with Bounding Map for Universal Lesion Detection
Universal Lesion Detection (ULD) in computed tomography plays an essenti...
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Generalizable Limited-Angle CT Reconstruction via Sinogram Extrapolation
Computed tomography (CT) reconstruction from X-ray projections acquired ...
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Universal Undersampled MRI Reconstruction
Deep neural networks have been extensively studied for undersampled MRI ...
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You Only Learn Once: Universal Anatomical Landmark Detection
Detecting anatomical landmarks in medical images plays an essential role...
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U-DuDoNet: Unpaired dual-domain network for CT metal artifact reduction
Recently, both supervised and unsupervised deep learning methods have be...
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One-Shot Medical Landmark Detection
The success of deep learning methods relies on the availability of a lar...
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Incremental Learning for Multi-organ Segmentation with Partially Labeled Datasets
There exists a large number of datasets for organ segmentation, which ar...
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Deep reinforcement learning in medical imaging: A literature review
Deep reinforcement learning (DRL) augments the reinforcement learning fr...
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A Hierarchical Feature Constraint to Camouflage Medical Adversarial Attacks
Deep neural networks (DNNs) for medical images are extremely vulnerable ...
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CT Film Recovery via Disentangling Geometric Deformation and Illumination Variation: Simulated Datasets and Deep Models
While medical images such as computed tomography (CT) are stored in DICO...
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Deep Learning to Segment Pelvic Bones: Large-scale CT Datasets and Baseline Models
Purpose: Pelvic bone segmentation in CT has always been an essential ste...
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Aggregative Self-Supervised Feature Learning
Self-supervised learning (SSL) is an efficient approach that addresses t...
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Label-Free Segmentation of COVID-19 Lesions in Lung CT
Scarcity of annotated images hampers the building of automated solution ...
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Limited View Tomographic Reconstruction Using a Deep Recurrent Framework with Residual Dense Spatial-Channel Attention Network and Sinogram Consistency
Limited view tomographic reconstruction aims to reconstruct a tomographi...
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Bounding Maps for Universal Lesion Detection
Universal Lesion Detection (ULD) in computed tomography plays an essenti...
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Miss the Point: Targeted Adversarial Attack on Multiple Landmark Detection
Recent methods in multiple landmark detection based on deep convolutiona...
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Marginal loss and exclusion loss for partially supervised multi-organ segmentation
Annotating multiple organs in medical images is both costly and time-con...
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Embedding Task Knowledge into 3D Neural Networks via Self-supervised Learning
Deep learning highly relies on the amount of annotated data. However, an...
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Human Recognition Using Face in Computed Tomography
With the mushrooming use of computed tomography (CT) images in clinical ...
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DuDoRNet: Learning a Dual-Domain Recurrent Network for Fast MRI Reconstruction with Deep T1 Prior
MRI with multiple protocols is commonly used for diagnosis, but it suffe...
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First image then video: A two-stage network for spatiotemporal video denoising
Video denoising is to remove noise from noise-corrupted data, thus recov...
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DuDoNet++: Encoding mask projection to reduce CT metal artifacts
CT metal artifact reduction (MAR) is a notoriously challenging task beca...
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Joint Unsupervised Learning for the Vertebra Segmentation, Artifact Reduction and Modality Translation of CBCT Images
We investigate the unsupervised learning of the vertebra segmentation, a...
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Learning a Self-inverse Network for Unpaired Bidirectional Image-to-image Translation
Recently image-to-image translation has attracted significant interests ...
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Towards Learning a Self-inverse Network for Bidirectional Image-to-image Translation
The one-to-one mapping is necessary for many bidirectional image-to-imag...
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Towards multi-sequence MR image recovery from undersampled k-space data
Undersampled MR image recovery has been widely studied for accelerated M...
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Deep Slice Interpolation via Marginal Super-Resolution, Fusion and Refinement
We propose a marginal super-resolution (MSR) approach based on 2D convol...
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ADN: Artifact Disentanglement Network for Unsupervised Metal Artifact Reduction
Current deep neural network based approaches to computed tomography (CT)...
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Generative Mask Pyramid Network forCT/CBCT Metal Artifact Reduction with Joint Projection-Sinogram Correction
A conventional approach to computed tomography (CT) or cone beam CT (CBC...
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Generative Mask Pyramid Network for CT/CBCT Metal Artifact Reduction with Joint Projection-Sinogram Correction
A conventional approach to computed tomography (CT) or cone beam CT (CBC...
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Artifact Disentanglement Network for Unsupervised Metal Artifact Reduction
Current deep neural network based approaches to computed tomography (CT)...
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Multiview 2D/3D Rigid Registration via a Point-Of-Interest Network for Tracking and Triangulation (POINT^2)
We propose to tackle the problem of multiview 2D/3D rigid registration f...
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Face Completion with Semantic Knowledge and Collaborative Adversarial Learning
Unlike a conventional background inpainting approach that infers a missi...
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Combo Loss: Handling Input and Output Imbalance in Multi-Organ Segmentation
Simultaneous segmentation of multiple organs from different medical imag...
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Select, Attend, and Transfer: Light, Learnable Skip Connections
Skip connections in deep networks have improved both segmentation and cl...
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3D Anisotropic Hybrid Network: Transferring Convolutional Features from 2D Images to 3D Anisotropic Volumes
While deep convolutional neural networks (CNN) have been successfully ap...
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Automatic Liver Segmentation Using an Adversarial Image-to-Image Network
Automatic liver segmentation in 3D medical images is essential in many c...
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Automatic Vertebra Labeling in Large-Scale 3D CT using Deep Image-to-Image Network with Message Passing and Sparsity Regularization
Automatic localization and labeling of vertebra in 3D medical images pla...
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Iterative Multi-domain Regularized Deep Learning for Anatomical Structure Detection and Segmentation from Ultrasound Images
Accurate detection and segmentation of anatomical structures from ultras...
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