research
∙
07/05/2023
Source Identification: A Self-Supervision Task for Dense Prediction
The paradigm of self-supervision focuses on representation learning from...
share
research
∙
04/09/2023
On the dice loss gradient and the ways to mimic it
In the past few years, in the context of fully-supervised semantic segme...
research
∙
09/14/2022
Label Refinement Network from Synthetic Error Augmentation for Medical Image Segmentation
Deep convolutional neural networks for image segmentation do not learn t...
research
∙
09/22/2021
A Quantitative Comparison of Epistemic Uncertainty Maps Applied to Multi-Class Segmentation
Uncertainty assessment has gained rapid interest in medical image analys...
research
∙
11/20/2020
Crowdsourcing Airway Annotations in Chest Computed Tomography Images
Measuring airways in chest computed tomography (CT) scans is important f...
research
∙
06/26/2020
Region-of-interest guided Supervoxel Inpainting for Self-supervision
Self-supervised learning has proven to be invaluable in making best use ...
research
∙
11/04/2019
Semi-Supervised Medical Image Segmentation via Learning Consistency under Transformations
The scarcity of labeled data often limits the application of supervised ...
research
∙
11/04/2019
Automated Estimation of the Spinal Curvature via Spine Centerline Extraction with Ensembles of Cascaded Neural Networks
Scoliosis is a condition defined by an abnormal spinal curvature. For di...
research
∙
09/19/2019
APIR-Net: Autocalibrated Parallel Imaging Reconstruction using a Neural Network
Deep learning has been successfully demonstrated in MRI reconstruction o...
research
∙
08/22/2019
A joint 3D UNet-Graph Neural Network-based method for Airway Segmentation from chest CTs
We present an end-to-end deep learning segmentation method by combining ...
research
∙
07/29/2019
Automated Lesion Detection by Regressing Intensity-Based Distance with a Neural Network
Localization of focal vascular lesions on brain MRI is an important comp...
research
∙
07/29/2019
Multi-Task Attention-Based Semi-Supervised Learning for Medical Image Segmentation
We propose a novel semi-supervised image segmentation method that simult...
research
∙
07/01/2019
Automated Image Registration Quality Assessment Utilizing Deep-learning based Ventricle Extraction in Clinical Data
Registration is a core component of many imaging pipelines. In case of c...
research
∙
06/05/2019
Weakly Supervised Object Detection with 2D and 3D Regression Neural Networks
Weakly supervised detection methods can infer the location of target obj...
research
∙
03/11/2019
A cross-center smoothness prior for variational Bayesian brain tissue segmentation
Suppose one is faced with the challenge of tissue segmentation in MR ima...
research
∙
03/08/2019
Event-Based Modeling with High-Dimensional Imaging Biomarkers for Estimating Spatial Progression of Dementia
Event-based models (EBM) are a class of disease progression models that ...
research
∙
11/21/2018
Graph Refinement based Tree Extraction using Mean-Field Networks and Graph Neural Networks
Graph refinement, or the task of obtaining subgraphs of interest from ov...
research
∙
11/08/2018
An End-to-end Approach to Semantic Segmentation with 3D CNN and Posterior-CRF in Medical Images
Fully-connected Conditional Random Field (CRF) is often used as post-pro...
research
∙
10/17/2018
Learning to quantify emphysema extent: What labels do we need?
Accurate assessment of pulmonary emphysema is crucial to assess disease ...
research
∙
07/23/2018
Deep Learning from Label Proportions for Emphysema Quantification
We propose an end-to-end deep learning method that learns to estimate em...
research
∙
07/12/2018
Hydranet: Data Augmentation for Regression Neural Networks
Despite recent efforts, deep learning techniques remain often heavily de...
research
∙
06/23/2018
Extracting Tree-structures in CT data by Tracking Multiple Statistically Ranked Hypotheses
In this work, we adapt a method based on multiple hypothesis tracking (M...
research
∙
06/19/2018
Feature learning based on visual similarity triplets in medical image analysis: A case study of emphysema in chest CT scans
Supervised feature learning using convolutional neural networks (CNNs) c...
research
∙
04/17/2018
Not-so-supervised: a survey of semi-supervised, multi-instance, and transfer learning in medical image analysis
Machine learning (ML) algorithms have made a tremendous impact in the fi...
research
∙
04/12/2018
Extraction of Airways using Graph Neural Networks
We present extraction of tree structures, such as airways, from image da...
research
∙
04/10/2018
Mean Field Network based Graph Refinement with application to Airway Tree Extraction
We present tree extraction in 3D images as a graph refinement task, of o...
research
∙
03/21/2018
Quantification of Lung Abnormalities in Cystic Fibrosis using Deep Networks
Cystic fibrosis is a genetic disease which may appear in early life with...
research
∙
02/16/2018
3D Regression Neural Network for the Quantification of Enlarged Perivascular Spaces in Brain MRI
Enlarged perivascular spaces (EPVS) in the brain are an emerging imaging...
research
∙
08/07/2017
Extraction of Airways with Probabilistic State-space Models and Bayesian Smoothing
Segmenting tree structures is common in several image processing applica...
research
∙
06/07/2017
Early Experiences with Crowdsourcing Airway Annotations in Chest CT
Measuring airways in chest computed tomography (CT) images is important ...
research
∙
06/07/2017
Automatic Emphysema Detection using Weakly Labeled HRCT Lung Images
A method for automatically quantifying emphysema regions using High-Reso...
research
∙
06/04/2017
Segmentation of Intracranial Arterial Calcification with Deeply Supervised Residual Dropout Networks
Intracranial carotid artery calcification (ICAC) is a major risk factor ...
research
∙
05/22/2017
GP-Unet: Lesion Detection from Weak Labels with a 3D Regression Network
We propose a novel convolutional neural network for lesion detection fro...
research
∙
03/15/2017
Label Stability in Multiple Instance Learning
We address the problem of instance label stability in multiple instance ...
research
∙
03/15/2017
Transfer Learning by Asymmetric Image Weighting for Segmentation across Scanners
Supervised learning has been very successful for automatic segmentation ...
research
∙
03/15/2017
Classification of COPD with Multiple Instance Learning
Chronic obstructive pulmonary disease (COPD) is a lung disease where ear...
research
∙
01/18/2017
Transfer learning for multi-center classification of chronic obstructive pulmonary disease
Chronic obstructive pulmonary disease (COPD) is a lung disease which can...
research
∙
11/24/2016
Extraction of airway trees using multiple hypothesis tracking and template matching
Knowledge of airway tree morphology has important clinical applications ...
research
∙
03/29/2013
Geometric tree kernels: Classification of COPD from airway tree geometry
Methodological contributions: This paper introduces a family of kernels ...
research
∙
07/23/2012
