Quantitative analysis of tumour characteristics based on medical imaging is an emerging
field of research. In recent years, quantitative imaging features derived from CT, positron …

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 …

Abstract Machine learning approaches are increasingly successful in image-based
diagnosis, disease prognosis, and risk assessment. This paper highlights new research …

Rationale: Deep learning is a powerful tool that may allow for improved outcome prediction.
Objectives: To determine if deep learning, specifically convolutional neural network (CNN) …

Cognitive impairment in patients with Alzheimer's disease (AD) is associated with reduction
in hippocampal volume in magnetic resonance imaging (MRI). However, it is unknown …

This paper presents a brain T1-weighted structural magnetic resonance imaging (MRI)
biomarker that combines several individual MRI biomarkers (cortical thickness …

Chronic airflow limitation is the common denominator of patients with chronic obstructive
pulmonary disease (COPD). However, it is not possible to predict morbidity and mortality of …

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 …

Alzheimer's disease (AD) is an irreversible neurodegenerative brain disorder that degrades
the memory and cognitive ability in elderly people. The main reason for memory loss and …

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 …