Deep learning for screening of interstitial lung disease patterns in high-resolution CT images.

Journal: Clinical radiology

Published Date: Feb 16, 2020

AIM: To develop a screening tool for the detection of interstitial lung disease (ILD) patterns using a deep-learning method.

S Agarwala

Department of Computer Science and Engineering, National Institute of Technology Durgapur, Durgapur, 713209, India.
M Kale

Department of Electronics and Electrical Communication Engineering, Indian Institute of Technology Kharagpur, Kharagpur, 721302, India.
D Kumar

Indian Council of Agricultural Research-Indian Agricultural Statistics Research Institute, New Delhi, India.
R Swaroop

Department of Computer Science and Engineering, National Institute of Technology Durgapur, Durgapur, 713209, India.
A Kumar

Department of Chemical Engineering, College of Engineering, Qatar University Doha 2713 Qatar.
A Kumar Dhara

Department of Electrical Engineering, National Institute of Technology Durgapur, Durgapur, 713209, India. Electronic address: ashis.dhara@ee.nitdgp.ac.inAim.
S Basu Thakur

Department of Chest Medicine, Medical College Kolkata, 700073, India.
A Sadhu

Department of Radiology, Medical College Kolkata, 700073, India.
D Nandi

Department of Computer Science and Engineering, National Institute of Technology Durgapur, Durgapur, 713209, India.

Datasets as Topic Deep Learning Humans Lung Diseases, Interstitial Radiographic Image Interpretation, Computer-Assisted Sensitivity and Specificity Tomography, X-Ray Computed

View on PubMed Access via DOI PubMed (32075744)