Stabilizing deep tomographic reconstruction: Part B. Convergence analysis and adversarial attacks
Weiwen Wu, Dianlin Hu, Wenxiang Cong, Hongming Shan, Shaoyu Wang, Chuang Niu, Pingkun Yan, Hengyong Yu, Varut Vardhanabhuti, Ge Wang
Abstract
in the perspective of an iterative reconstruction procedure and [2] a pseudo-inverse is used for a total variation operator H). Also, we present adversarial attack algorithms to perturb the selected reconstruction networks respectively and, more importantly, to attack the ACID workflow as a whole. Finally, we show the numerical convergence of the ACID iteration in terms of the Lipschitz constant and the local stability against noise.
Topics & Concepts
Lipschitz continuityIterative reconstructionConvergence (economics)Bounded functionInverseInverse problemComputer scienceMathematical optimizationTomographic reconstructionAlgorithmMathematicsApplied mathematicsArtificial intelligenceMathematical analysisEconomic growthGeometryEconomicsMedical Imaging Techniques and ApplicationsAdvanced X-ray and CT ImagingAdvanced MRI Techniques and Applications