Title :
An image analysis method for quantification of idiopathic pulmonary fibrosis
Author :
Acharya, Mekhala ; Kinser, Jason ; Nathan, Steven ; Albano, Marcia C. ; Schlegel, Lori
Author_Institution :
Sch. of Syst. Biol., George Mason Univ., Manassas, VA, USA
Abstract :
Diagnosis of IPF (idiopathic pulmonary fibrosis) is based on clinical, radiographic and histopathologic evaluations. In this paper we present an adaptive thresholding algorithm and utilize quantitative CT indexes to correlate IPF with pulmonary abnormality. Simulation results demonstrate that this algorithm performs well in identified IPF images. However the absence of gold standards makes quantification challenging for early stage images of IPF and blinded images.
Keywords :
computerised tomography; diseases; feature extraction; image classification; learning (artificial intelligence); medical image processing; patient diagnosis; CT index; IPF diagnosis; IPF with pulmonary abnormality; adaptive thresholding algorithm; blinded image; clinical evaluation; computerised tomography; histopathologic evaluation; idiopathic pulmonary fibrosis quantification; image analysis method; radiographic evaluation; Computed tomography; Diseases; Feature extraction; Histograms; Indexes; Lungs; Measurement; Idopatic pulmonary fibrosis; adaptive multiple feature metshod; high resolution computed tomography;
Conference_Titel :
Applied Imagery Pattern Recognition Workshop (AIPR), 2011 IEEE
Conference_Location :
Washington, DC
Print_ISBN :
978-1-4673-0215-9
DOI :
10.1109/AIPR.2011.6176357
