scholarly journals Interstitial lung diseases : Advances in diagnosis and treatment.Concept, etiology and classification of interstitial lung diseases.

1994 ◽  
Vol 83 (5) ◽  
pp. 705-711 ◽  
Author(s):  
SATOSHI KITAMURA
Keyword(s):  
Lung Diseases ◽  
Interstitial Lung Diseases

Automated detection and classification of interstitial lung diseases from low-dose CT images

2004 ◽  
Author(s):  
Bin Zheng ◽  
Joseph K. Leader ◽  
Carl R. Fuhrman ◽  
Frank C. Sciurba ◽  
David Gur
Keyword(s):  
Lung Diseases ◽  
Low Dose ◽  
Ct Images ◽  
Interstitial Lung Diseases ◽  
Automated Detection ◽  
Low Dose Ct

scholarly journals A lung graph model for the classification of interstitial lung diseases on CT images

2019 ◽  
Author(s):  
Guillaume Vanoost ◽  
Adrien Depeursinge ◽  
Yashin Dicente Cid ◽  
Daniel Rubin
Keyword(s):  
Lung Diseases ◽  
Graph Model ◽  
Ct Images ◽  
Interstitial Lung Diseases

scholarly journals Current concepts and dilemmas in idiopathic interstitial pneumonias

F1000Research ◽  
2016 ◽  
Vol 5 ◽  
pp. 2661 ◽  
Author(s):  
Jay H. Ryu ◽  
Teng Moua ◽  
Natalya Azadeh ◽  
Misbah Baqir ◽  
Eunhee S. Yi
Keyword(s):  
Lung Diseases ◽  
Interstitial Lung Diseases ◽  
Clinical Applications ◽  
Idiopathic Interstitial Pneumonias ◽  
Initial Description ◽  
Recent Version

Idiopathic interstitial pneumonias comprise approximately one-third of interstitial lung diseases (also called diffuse parenchymal infiltrative lung diseases). The classification of idiopathic interstitial pneumonias has undergone several revisions since the initial description of 40 years ago, and the most recent version was published in 2013. Although some aspects have been clarified, this group of heterogeneous disorders continues to be a source of confusion and misunderstanding in clinical applications. In this article, we explore several topical themes in the evaluation and management of patients with idiopathic interstitial pneumonias.

scholarly journals Pattern classification of interstitial lung disease in high resolution clinical datasets: A systematic review

2018 ◽  
Vol 7 (2.7) ◽  
pp. 114
Author(s):  
S Ummay Atiya ◽  
N V.K Ramesh
Keyword(s):  
Computed Tomography ◽  
High Resolution ◽  
Lung Diseases ◽  
Interstitial Lung Diseases ◽  
High Resolution Computed Tomography ◽  
Different Types ◽  
Deep Convolution Neural Network ◽  
Paper Review ◽  
The Many

Automated tissues characterization helps to diagnosis the various diseases including Interstitial lung diseases (ILD). The various features and the several classifiers are used in categorize the different layers depend on the pattern presented in the image. The different types of diseases may occur in the lungs and some of the diseases happen to leave the scars. These scars can be found in the High Resolution Computed Tomography (HRCT) and have different pattern. The different diseases cause the different pattern in the images and these is classified using the efficient classifier that helps to diagnosis the diseases. In this paper, review for the many researches regarding to the classification of the different pattern from the Computed Tomography (CT) images is presented. The evaluation of the efficiency of the methods in terms of classifier and database used for the research is made. The Deep Convolution Neural Network (CNN) provides the promising classifier efficiency compared to the other researches for different pattern. In general, there are five types of pattern is classified: Healthy, ground glass, honeycomb, Fibrosis, and emphysema.

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