AUTOCORRECTING RECONSTRUCTION FOR FLEXIBLE CT SCANNERS

Nanotechnology researchers are developing miniature, low-power X-ray devices. These innovations might revolutionize the world of computed tomography (CT). Tiny X-ray emitters and detectors could be embedded on a flexible sheet and deployed around a body part to acquire CT data at the scene of an accident. However, the irregular geometry of such a scanner makes the reconstruction problem more challenging. Moreover, measurement errors in the positions of the emitters and detectors would limit the quality of the resulting images. We propose a robust reconstruction methodology that can automatically correct for small errors in the CT scanner geometry. The method uses a simple optimization scheme to minimize the entropy of the reconstructed image. Test cases suggest that this is a viable approach to robust reconstruction for flexible CT scanners