title: Tissue-specific sparse deconvolution for low-dose CT perfusion.
abstract: Sparse perfusion deconvolution has been recently proposed to effectively improve the image quality and diagnostic accuracy of low-dose perfusion CT by extracting the complementary information from the high-dose perfusion maps to restore the low-dose using a joint spatio-temporal model. However the low-contrast tissue classes where infarct core and ischemic penumbra usually occur in cerebral perfusion CT tend to be over-smoothed, leading to loss of essential biomarkers. In this paper, we extend this line of work by introducing tissue-specific sparse deconvolution to preserve the subtle perfusion information in the low-contrast tissue classes by learning tissue-specific dictionaries for each tissue class, and restore the low-dose perfusion maps by joining the tissue segments reconstructed from the corresponding dictionaries. Extensive validation on clinical datasets of patients with cerebrovascular disease demonstrates the superior performance of our proposed method with the advantage of better differentiation between abnormal and normal tissue in these patients.
authors: Department of Electrical and Computer Engineering, Cornell University, Ithaca, NY, USA.
authors: Ruogu
authors: R
authors: Fang
authors: Department of Electrical and Computer Engineering, Cornell University, Ithaca, NY, USA.
authors: Tsuhan
authors: T
authors: Chen
authors: Department of Radiology, Weill Cornell Medical College, New York, NY, USA.
authors: Pina C
authors: PC
authors: Sanelli
mesh_terms: D000465:Algorithms; D001783:Blood Flow Velocity; D001921:Brain / Q000000981:diagnostic imaging / Q000503:physiopathology; D002545:Brain Ischemia / Q000000981:diagnostic imaging* / Q000503:physiopathology*; D002533:Cerebral Angiography / Q000379:methods*; D002560:Cerebrovascular Circulation; D006801:Humans; D055420:Perfusion Imaging / Q000379:methods*; D011856:Radiographic Image Enhancement / Q000379:methods; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014057:Tomography, X-Ray Computed / Q000379:methods*