On reconstruction of binary images by efficient sample-based parameterization in applications for electrical impedance tomography

An efficient computational approach for optimal reconstruction of binary-type images suitable models in various applications including biomedical imaging is developed and validated. The methodology includes derivative-free optimization supported by a set sample solutions with customized geometry generated synthetically. reduced dimensional control space organized based on contributions from individual samples the parameterization obtained description samples' geometry. entire framework has an easy-to-follow design due to nominal number tuning parameters. High efficiency time achieved through applying coordinate descent method work controls predefined custom order. Performance complete tested 2D inverse problems detecting inclusions or defective regions electrical impedance tomography (EIT). results demonstrate performance high potential improving overall quality EIT-based procedures applications.