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08/08/2023
ConDistFL: Conditional Distillation for Federated Learning from Partially Annotated Data
Developing a generalized segmentation model capable of simultaneously de...
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03/28/2023
Communication-Efficient Vertical Federated Learning with Limited Overlapping Samples
Federated learning is a popular collaborative learning approach that ena...
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11/04/2022
MONAI: An open-source framework for deep learning in healthcare
Artificial Intelligence (AI) is having a tremendous impact across most a...
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10/24/2022
NVIDIA FLARE: Federated Learning from Simulation to Real-World
Federated learning (FL) enables the building of robust and generalizable...
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09/13/2022
Warm Start Active Learning with Proxy Labels & Selection via Semi-Supervised Fine-Tuning
Which volume to annotate next is a challenging problem in building medic...
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08/22/2022
Split-U-Net: Preventing Data Leakage in Split Learning for Collaborative Multi-Modal Brain Tumor Segmentation
Split learning (SL) has been proposed to train deep learning models in a...
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03/23/2022
MONAI Label: A framework for AI-assisted Interactive Labeling of 3D Medical Images
The lack of annotated datasets is a major challenge in training new task...
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03/12/2022
Auto-FedRL: Federated Hyperparameter Optimization for Multi-institutional Medical Image Segmentation
Federated learning (FL) is a distributed machine learning technique that...
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02/14/2022
Do Gradient Inversion Attacks Make Federated Learning Unsafe?
Federated learning (FL) allows the collaborative training of AI models w...
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11/15/2021
T-AutoML: Automated Machine Learning for Lesion Segmentation using Transformers in 3D Medical Imaging
Lesion segmentation in medical imaging has been an important topic in cl...
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08/19/2021
Multi-task Federated Learning for Heterogeneous Pancreas Segmentation
Federated learning (FL) for medical image segmentation becomes more chal...
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07/16/2021
Federated Whole Prostate Segmentation in MRI with Personalized Neural Architectures
Building robust deep learning-based models requires diverse training dat...
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01/07/2021
Diminishing Uncertainty within the Training Pool: Active Learning for Medical Image Segmentation
Active learning is a unique abstraction of machine learning techniques w...
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11/23/2020
Federated Semi-Supervised Learning for COVID Region Segmentation in Chest CT using Multi-National Data from China, Italy, Japan
The recent outbreak of COVID-19 has led to urgent needs for reliable dia...
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09/28/2020
Automated Pancreas Segmentation Using Multi-institutional Collaborative Deep Learning
The performance of deep learning-based methods strongly relies on the nu...
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09/25/2020
Going to Extremes: Weakly Supervised Medical Image Segmentation
Medical image annotation is a major hurdle for developing precise and ro...
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04/20/2020
Colonoscope tracking method based on shape estimation network
This paper presents a colonoscope tracking method utilizing a colon shap...
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08/05/2019
Precise Estimation of Renal Vascular Dominant Regions Using Spatially Aware Fully Convolutional Networks, Tensor-Cut and Voronoi Diagrams
This paper presents a new approach for precisely estimating the renal va...
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06/08/2018
3D FCN Feature Driven Regression Forest-Based Pancreas Localization and Segmentation
This paper presents a fully automated atlas-based pancreas segmentation ...
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06/06/2018
A multi-scale pyramid of 3D fully convolutional networks for abdominal multi-organ segmentation
Recent advances in deep learning, like 3D fully convolutional networks (...
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04/11/2018
Unsupervised Segmentation of 3D Medical Images Based on Clustering and Deep Representation Learning
This paper presents a novel unsupervised segmentation method for 3D medi...
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04/11/2018
Unsupervised Pathology Image Segmentation Using Representation Learning with Spherical K-means
This paper presents a novel method for unsupervised segmentation of path...
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03/23/2018
Deep learning and its application to medical image segmentation
One of the most common tasks in medical imaging is semantic segmentation...
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03/14/2018
An application of cascaded 3D fully convolutional networks for medical image segmentation
Recent advances in 3D fully convolutional networks (FCN) have made it fe...
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01/18/2018
On the influence of Dice loss function in multi-class organ segmentation of abdominal CT using 3D fully convolutional networks
Deep learning-based methods achieved impressive results for the segmenta...
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03/15/2017
Comparison of the Deep-Learning-Based Automated Segmentation Methods for the Head Sectioned Images of the Virtual Korean Human Project
This paper presents an end-to-end pixelwise fully automated segmentation...
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02/27/2017
Multi-scale Image Fusion Between Pre-operative Clinical CT and X-ray Microtomography of Lung Pathology
Computational anatomy allows the quantitative analysis of organs in medi...
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01/31/2017
Spatial Aggregation of Holistically-Nested Convolutional Neural Networks for Automated Pancreas Localization and Segmentation
Accurate and automatic organ segmentation from 3D radiological scans is ...
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06/24/2016
Spatial Aggregation of Holistically-Nested Networks for Automated Pancreas Segmentation
Accurate automatic organ segmentation is an important yet challenging pr...
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02/10/2016
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
Remarkable progress has been made in image recognition, primarily due to...
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02/01/2016
Improving Vertebra Segmentation through Joint Vertebra-Rib Atlases
Accurate spine segmentation allows for improved identification and quant...
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01/29/2016
Deep convolutional networks for automated detection of posterior-element fractures on spine CT
Injuries of the spine, and its posterior elements in particular, are a c...
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01/13/2016
Multi-Atlas Segmentation with Joint Label Fusion of Osteoporotic Vertebral Compression Fractures on CT
The precise and accurate segmentation of the vertebral column is essenti...
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06/22/2015
DeepOrgan: Multi-level Deep Convolutional Networks for Automated Pancreas Segmentation
Automatic organ segmentation is an important yet challenging problem for...
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05/12/2015
Improving Computer-aided Detection using Convolutional Neural Networks and Random View Aggregation
Automated computer-aided detection (CADe) in medical imaging has been an...
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04/15/2015
Anatomy-specific classification of medical images using deep convolutional nets
Automated classification of human anatomy is an important prerequisite f...
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04/15/2015
Deep convolutional networks for pancreas segmentation in CT imaging
Automatic organ segmentation is an important prerequisite for many compu...
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01/15/2015
Computer-assisted polyp matching between optical colonoscopy and CT colonography: a phantom study
Potentially precancerous polyps detected with CT colonography (CTC) need...
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07/22/2014
Detection of Sclerotic Spine Metastases via Random Aggregation of Deep Convolutional Neural Network Classifications
Automated detection of sclerotic metastases (bone lesions) in Computed T...
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06/06/2014