Quantitative texture analysis of normal and abnormal lung tissue for low dose CT reconstruction using the tissue-specific texture prior

Yongfeng Gao; Siming Lu; Amit Gupta; Haifang Li; John Ferretti; Zhengrong Liang

doi:10.1117/12.2582129

15 February 2021 Quantitative texture analysis of normal and abnormal lung tissue for low dose CT reconstruction using the tissue-specific texture prior

Yongfeng Gao, Siming Lu, Amit Gupta, Haifang Li, John Ferretti, Zhengrong Liang

Author Affiliations +

Proceedings Volume 11595, Medical Imaging 2021: Physics of Medical Imaging; 115953O (2021) https://doi.org/10.1117/12.2582129
Event: SPIE Medical Imaging, 2021, Online Only

Conference Poster

Abstract

Screening is an effective way to detect lung cancer early and can improve the survival rate significantly. The low-dose computed tomography (LdCT) is demanding for lung screening to ensure the exam radiation as low as reasonably possible. The statistical image reconstruction has shown great advantages in LdCT imaging, where many types of priors can be used as constrain for optimal images. The tissue-specific Markov random field (MRF) type texture prior (MRFt) was proposed in our previous work to address the clinical related texture information. For the chest scans, four tissue texture were extracted from regions of lung, bone, fat and muscle respectively. In this work, we focus on the region of interest, i.e. lung for the lung cancer screening. The quantitative texture analysis of normal and abnormal lung tissue was performed to address the following issues of the proposed MRFt model: (1) a more comprehensive understanding of the lung tissue texture (2) what MRF prior we should use for the abnormal lung tissue. Experiments results showed that normal lung tissue has texture similarity among different subjects. The robust similarity among humans laid the feasibility of building the lung tissue database for the LdCT imaging which has no previous FdCT scans. Different abnormal lung tissue varies significantly. There is no way to get the prior knowledge of lung nodules until the CT exam was performed.

Conference Presentation

Citation Download Citation

Yongfeng Gao, Siming Lu, Amit Gupta, Haifang Li, John Ferretti, and Zhengrong Liang "Quantitative texture analysis of normal and abnormal lung tissue for low dose CT reconstruction using the tissue-specific texture prior", Proc. SPIE 11595, Medical Imaging 2021: Physics of Medical Imaging, 115953O (15 February 2021); https://doi.org/10.1117/12.2582129

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