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17 October 2022 Fully utilizing contrast enhancement on lung tissue as a novel basis material for lung nodule characterization by multi-energy CT
Shaojie Chang, Yongfeng Gao, Marc J. Pomeroy, Ti Bai, Hao Zhang, Zhengrong Liang
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Proceedings Volume 12304, 7th International Conference on Image Formation in X-Ray Computed Tomography; 1230429 (2022) https://doi.org/10.1117/12.2646550
Event: Seventh International Conference on Image Formation in X-Ray Computed Tomography (ICIFXCT 2022), 2022, Baltimore, United States
Abstract
Based on well-established X-ray physics in computed tomography (CT) imaging, the spectral responses of different materials contained in lesions are different, which brings richer contrast information at various energy bins. Hence, obtaining the material decomposition of different tissue types and exploring its spectral information for lesion diagnosis becomes extremely valuable. The lungs are housed within the torso and consist of three natural materials, i.e., soft tissue, bone, and lung tissue. To benefit the lung nodule differentiation, this study innovatively proposed to use lung tissue as one basis material along with soft tissue and bone. This set of basis materials will yield a more accurate composition analysis of lung nodules and benefit the following differentiation. Moreover, a corresponding machine learning (ML)-based computer-aided diagnosis framework for lung nodule classification is also proposed and used for evaluation. Experimental results show the advantages of the virtual monoenergetic images (VMIs) generated with lung tissue material over the VMIs without lung tissue and conventional CT images in differentiating the malignancy from benign lung nodules. The gain of 9.63% in area under the receiver operating characteristic curve (AUC) scores indicated that the energy-enhanced tissue features from lung tissue have a great potential to improve lung nodule diagnosis performance.
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Shaojie Chang, Yongfeng Gao, Marc J. Pomeroy, Ti Bai, Hao Zhang, and Zhengrong Liang "Fully utilizing contrast enhancement on lung tissue as a novel basis material for lung nodule characterization by multi-energy CT", Proc. SPIE 12304, 7th International Conference on Image Formation in X-Ray Computed Tomography, 1230429 (17 October 2022); https://doi.org/10.1117/12.2646550
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KEYWORDS
Tissues
Lung
Computer aided diagnosis and therapy
Bone
X-ray computed tomography
Computed tomography
Signal attenuation
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