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Found 14 papers, 2 papers with code
Evaluation of Mean Shift, ComBat, and CycleGAN for Harmonizing Brain Connectivity Matrices Across Sites
First, we plotted the graph measures and used coefficient of variation (CoV) and the Mann-Whitney U test to evaluate different methods' effectiveness in removing site effects on the matrices and the derived graph measures.
Inter-vendor harmonization of Computed Tomography (CT) reconstruction kernels using unpaired image translation
In this study, we adopt an unpaired image translation approach to investigate harmonization between and across reconstruction kernels from different manufacturers by constructing a multipath cycle generative adversarial network (GAN).
Diffeomorphic Spatial Transformer Networks
In this paper we propose a spatial transformer network where the spatial transformations are limited to the group of diffeomorphisms.
3D Convolutional Neural Networks Image Registration Based on Efficient Supervised Learning from Artificial Deformations
We propose a supervised nonrigid image registration method, trained using artificial displacement vector fields (DVF), for which we propose and compare three network architectures.
Direct Automatic Coronary Calcium Scoring in Cardiac and Chest CT
To meet demands of the increasing interest in quantification of CAC, i. e. coronary calcium scoring, especially as an unrequested finding for screening and research, automatic methods have been proposed.
Response monitoring of breast cancer on DCE-MRI using convolutional neural network-generated seed points and constrained volume growing
A constrained volume growing method uses these manually placed seed points as input and generates a tumor segmentation.
Automatic Segmentation of Thoracic Aorta Segments in Low-Dose Chest CT
Hence, we propose an automatic method to segment the ascending aorta, the aortic arch and the thoracic descending aorta in low-dose chest CT without contrast enhancement.
A Deep Learning Framework for Unsupervised Affine and Deformable Image Registration
To circumvent the need for predefined examples, and thereby to increase convenience of training ConvNets for image registration, we propose the Deep Learning Image Registration (DLIR) framework for \textit{unsupervised} affine and deformable image registration.
A Recurrent CNN for Automatic Detection and Classification of Coronary Artery Plaque and Stenosis in Coronary CT Angiography
The results demonstrate that automatic detection and classification of coronary artery plaque and stenosis are feasible.
Direct and Real-Time Cardiovascular Risk Prediction
The results demonstrate that real-time quantification of CAC burden in chest CT without the need for segmentation of CAC is possible.
Automatic Segmentation and Disease Classification Using Cardiac Cine MR Images
We propose a fully automatic method for segmentation and disease classification using cardiac cine MR images.
Deep MR to CT Synthesis using Unpaired Data
MR-only radiotherapy treatment planning requires accurate MR-to-CT synthesis.
Automatic Segmentation of the Left Ventricle in Cardiac CT Angiography Using Convolutional Neural Network
Subsequently, to obtain the segmentation of the LV, voxel classification is performed within the defined bounding box using a CNN.
