Automated segmentation of lungs with severe interstitial lung disease in CT.

Medical Physics
Jiahui WangQiang Li

Abstract

Accurate segmentation of lungs with severe interstitial lung disease (ILD) in thoracic computed tomography (CT) is an important and difficult task in the development of computer-aided diagnosis (CAD) systems. Therefore, we developed in this study a texture analysis-based method for accurate segmentation of lungs with severe ILD in multidetector CT scans. Our database consisted of 76 CT scans, including 31 normal cases and 45 abnormal cases with moderate or severe ILD. The lungs in three selected slices for each CT scan were first manually delineated by a medical physicist, and then confirmed or revised by an expert chest radiologist, and they were used as the reference standard for lung segmentation. To segment the lungs, we first employed a CT value thresholding technique to obtain an initial lung estimate, including normal and mild ILD lung parenchyma. We then used texture-feature images derived from the co-occurrence matrix to further identify abnormal lung regions with severe ILD. Finally, we combined the identified abnormal lung regions with the initial lungs to generate the final lung segmentation result. The overlap rate, volume agreement, mean absolute distance (MAD), and maximum absolute distance (dmax) between the aut...Continue Reading

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Citations

Jan 26, 2011·Physics in Medicine and Biology·Sang Cheol ParkBin Zheng
May 21, 2011·Current Opinion in Pulmonary Medicine·Prashant K Rohatgi
Feb 11, 2012·Medical Physics·Jiahui WangQiang Li
Aug 5, 2014·Medical Physics·Thessa T J P KockelkornBram van Ginneken
Mar 8, 2011·Academic Radiology·Nicholas J TustisonJames C Gee
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