Soutenance de thèse : Ting SU
Quantitative material decomposition methods for X-ray spectral CT
Doctorante : Ting SU
Laboratoire INSA : LVA
Ecole doctorale : ED160 E.E.A
X-ray computed tomography (X-ray CT) plays an important part in non-invasive imaging since its introduction. During the past few years, numerous technological advances in X-ray CT have been observed, including spectral CT, which uses Photon counting detectors (PCDs) to discriminate transmitted photons corresponding to selected energy bins in order to obtain spectral information with one data acquisition. Spectral CT enables to overcome many limitations of the previous techniques and opens up many new applications, among which quantitative material decomposition is the most investigated topic. A number of material decomposition methods have been reported and different experimental systems are under development for spectral CT. In the present work, we proposed the material decomposition methods for X-ray spectral CT based on patchwise regularization, including projection domain method and image domain method. Their performance were evaluated by spectral CT simulation studies with specific phantoms for different applications: (1) A computational human thorax phantom study for atherosclerosis imaging. The decomposition results of the proposed methods show that calcium and iodine can be well separated and quantified from soft tissues. (2) A poly(methyl methacrylate) (PMMA) phantom study for iron determination. The proposed methods can also discriminate iron from calcium, potassium and water. Meanwhile, different acquisition parameters of X-ray spectral CT, i.e. exposure factor and number of energy bins were simulated to investigate their influence on the decomposition performance. (3) A acrylonitrile- butadiene-styrene (ABS) phantom study for plastic sorting. The proposed projection method was applied to analyze data from the X-ray radioscopy with photon counting detector. Results show that 3 kinds of ABS materials with different flame retardant (FR) components can be well separated with high quantification accuracy of selected basis materials.
Amphithéâtre Est des Humanités (Villeurbanne)