Multi-constrained multi-material decomposition for dual energy CBCT

Qian Wang; Huiqiao Xie; Tonghe Wang; Justin Roper; Xiangyang Tang; Jeffrey D. Bradley; Tian Liu; Xiaofeng Yang

doi:10.1117/12.2654354

7 April 2023 Multi-constrained multi-material decomposition for dual energy CBCT

Qian Wang, Huiqiao Xie, Tonghe Wang, Justin Roper, Xiangyang Tang, Jeffrey D. Bradley, Tian Liu, Xiaofeng Yang

Proceedings Volume 12463, Medical Imaging 2023: Physics of Medical Imaging; 1246317 (2023) https://doi.org/10.1117/12.2654354
Event: SPIE Medical Imaging, 2023, San Diego, California, United States

Abstract

Cone-beam computed tomography (CBCT) is widely used in patient positioning for image-guided radiotherapy. However, compared to simulation CT, it suffers from scattering and beam hardening artifacts, Hounsfield units (HU) value inaccuracy, low tissue contrast, and high noise, which impede its potential applications, such as adaptive radiotherapy through online contouring and dose calculation. The capabilities of dual-energy CBCT (DE-CBCT) to overcome the aforementioned issues has been demonstrated in preclinical studies by introducing extra information along the spectral dimension and enabling the application of material decomposition. In this work, we propose a CT guided and sparsity constrained multi-material decomposition method for DE-CBCT to improve the image quality and quantitative accuracy of both DE-CBCT and material composition images. First, a local linear constraint is employed to mathematically describe the structure similarities between the DE-CBCT/ basis material and CT images, so that CT can effectively work as a guidance by introducing its superior image quality. Secondly, to regulate the multi-material decomposition process, low rank approximation with trace norm truncation is employed to limit the number of material bases and incorporate sum-to-one constraint to bound the material volume fractions. In addition, Mumford-Shah regularization in spatial domain is introduced for edge preservation and piece-wise smooth. Both phantom and patient studies demonstrate the superiority of the proposed method in image-quality, decomposition-accuracy, edge preservation, noise suppression and artifacts reduction, which further benefits some potential applications, such as online contouring and dose calculation for adaptive radiotherapy.

Conference Presentation

Citation Download Citation

Qian Wang, Huiqiao Xie, Tonghe Wang, Justin Roper, Xiangyang Tang, Jeffrey D. Bradley, Tian Liu, and Xiaofeng Yang "Multi-constrained multi-material decomposition for dual energy CBCT", Proc. SPIE 12463, Medical Imaging 2023: Physics of Medical Imaging, 1246317 (7 April 2023); https://doi.org/10.1117/12.2654354

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