Screening for lung cancer with low dose computed tomography can reduce mortality from
the disease by 20% in high risk smokers. This review covers the state of the art knowledge …

Subsolid pulmonary nodules occur less often than solid pulmonary nodules, but show a
much higher malignancy rate. Therefore, accurate detection of this type of pulmonary …

In this paper, we propose a new classification method for five categories of lung tissues in
high-resolution computed tomography (HRCT) images, with feature-based image patch …

Computer-aided detection and diagnosis (CAD) has been widely investigated to improve
radiologists׳ diagnostic accuracy in detecting and characterizing lung disease, as well as to …

We propose a new multiscale rotation-invariant convolutional neural network (MRCNN)
model for classifying various lung tissue types on high-resolution computed tomography …

Lung cancer at its earliest stage is typically manifested on computed tomography as a
pulmonary nodule, which could be detected by low-dose multidetector computed …

In this paper, we propose a novel classification method for the four types of lung nodules, ie,
well-circumscribed, vascularized, juxta-pleural, and pleural-tail, in low dose computed …

Medical images usually exhibit large intra-class variation and inter-class ambiguity in the
feature space, which could affect classification accuracy. To tackle this issue, we propose a …

AIM To develop a screening tool for the detection of interstitial lung disease (ILD) patterns
using a deep-learning method. MATERIALS AND METHODS A fully convolutional network …

In this paper, we propose a novel classification method for lung nodules from CT images
based on hybrid features. Towards nodules of different types, including well-circumscribed …