methods are direct (non-iterative) and therefore do not require repeated high-accuracy simulations to compute an image. Their real-time capabilities have recently been demonstrated in \[[@Dodd2014]\]. Here, we demonstrate that high quality absolute images can be computed quickly from D-bar methods, and that they are robust in the presence of the intrinsic system noise, as well as errors in electrode placement and domain shape. Absolute images are computed from experimental tank data using three D-bar methods, and the effects of errors in electrode location and domain shape are compared. The D-bar methods studied here are the $\operatorname{\mathbf{t}^{\mbox{\tiny{\textbf{exp}}}}}$ implementation of the D-bar method for real-valued conductivities based on the global uniqueness proof \[[@Nachman1996]\] with further developments and implementations in \[[@Siltanen2000; @Isaacson2004; @Knudsen2009]\], and two formulations of the D-bar method for complex-valued conductivities, [[also with the exp-approximation]{}]{} which are based on \[[@Francini2000; @Hamilton2012; @Herrera2015]\].

The first absolute images computed with a D-bar method were presented in \[[@Isaacson2004]\], where they were compared to absolute images computed using the NOSER \[[@Cheney1990a]\] algorithm. The images were found to be nearly free of the high conductivity artefacts along the boundary caused by the presence of the electrodes, but the target positions (agar heart and lungs) were of 