Fifty years of computer analysis in chest imaging: rule-based, machine learning, deep learning
B van Ginneken - Radiological physics and technology, 2017 - Springer
Half a century ago, the term “computer-aided diagnosis”(CAD) was introduced in the
scientific literature. Pulmonary imaging, with chest radiography and computed tomography …
scientific literature. Pulmonary imaging, with chest radiography and computed tomography …
[HTML][HTML] Human treelike tubular structure segmentation: A comprehensive review and future perspectives
Various structures in human physiology follow a treelike morphology, which often expresses
complexity at very fine scales. Examples of such structures are intrathoracic airways, retinal …
complexity at very fine scales. Examples of such structures are intrathoracic airways, retinal …
Extraction of airways from CT (EXACT'09)
This paper describes a framework for establishing a reference airway tree segmentation,
which was used to quantitatively evaluate 15 different airway tree extraction algorithms in a …
which was used to quantitatively evaluate 15 different airway tree extraction algorithms in a …
Improvement of fully automated airway segmentation on volumetric computed tomographic images using a 2.5 dimensional convolutional neural net
We propose a novel airway segmentation method in volumetric chest computed tomography
(CT) and evaluate its performance on multiple datasets. The segmentation is performed …
(CT) and evaluate its performance on multiple datasets. The segmentation is performed …
Artificial intelligence in diagnosis of obstructive lung disease: current status and future potential
Artificial intelligence in diagnosis of obstructive lung dis... : Current Opinion in Pulmonary
Medicine Artificial intelligence in diagnosis of obstructive lung disease: current status and future …
Medicine Artificial intelligence in diagnosis of obstructive lung disease: current status and future …
Comparing algorithms for automated vessel segmentation in computed tomography scans of the lung: the VESSEL12 study
Abstract The VESSEL12 (VESsel SEgmentation in the Lung) challenge objectively
compares the performance of different algorithms to identify vessels in thoracic computed …
compares the performance of different algorithms to identify vessels in thoracic computed …
Improving airway segmentation in computed tomography using leak detection with convolutional networks
We propose a novel method to improve airway segmentation in thoracic computed
tomography (CT) by detecting and removing leaks. Leak detection is formulated as a …
tomography (CT) by detecting and removing leaks. Leak detection is formulated as a …
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 a 3D UNet
architecture with a graph neural network (GNN) model. In this approach, the convolutional …
architecture with a graph neural network (GNN) model. In this approach, the convolutional …
Airwaynet: a voxel-connectivity aware approach for accurate airway segmentation using convolutional neural networks
Airway segmentation on CT scans is critical for pulmonary disease diagnosis and
endobronchial navigation. Manual extraction of airway requires strenuous efforts due to the …
endobronchial navigation. Manual extraction of airway requires strenuous efforts due to the …
Transfer learning for multicenter classification of chronic obstructive pulmonary disease
Chronic obstructive pulmonary disease (COPD) is a lung disease that can be quantified
using chest computed tomography scans. Recent studies have shown that COPD can be …
using chest computed tomography scans. Recent studies have shown that COPD can be …