Deep learning algorithms, in particular convolutional networks, have rapidly become a
methodology of choice for analyzing medical images. This paper reviews the major deep …

Quantitative analysis of thin-section CT of the chest has a growing role in the clinical
evaluation and management of diffuse lung diseases. This heterogeneous group includes …

Half a century ago, the term “computer-aided diagnosis”(CAD) was introduced in the
scientific literature. Pulmonary imaging, with chest radiography and computed tomography …

Accurate vertebrae segmentation from medical images plays an important role in clinical
tasks of surgical planning, diagnosis, kyphosis, scoliosis, degenerative disc disease …

Open international challenges are becoming the de facto standard for assessing computer
vision and image analysis algorithms. In recent years, new methods have extended the …

Deep learning is a genre of machine learning that allows computational models to learn
representations of data with multiple levels of abstraction using numerous processing layers …

The Genetic Epidemiology of Chronic Obstructive Pulmonary Disease (COPDGene) study,
which began in 2007, is an ongoing multicenter observational cohort study of more than …

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 …

Extensive research has been devoted to the segmentation of the coronary artery. However,
owing to its complex anatomical structure, it is extremely challenging to automatically …

We propose a novel airway segmentation method in volumetric chest computed tomography
(CT) and evaluate its performance on multiple datasets. The segmentation is performed …