Artifacts suppression in biomedical images using a guided filter

In this work, we further develop the method of tomography reconstruction of incomplete or corrupted data. Such data appear, for example, when tomographic projections acquisition fails or object leaves a detector's field of view. Our approach doesn't use regularizations or a priori information about the sample. It is based only on the hypothesis of the consistency of the sample in sinogram space and reconstruction space and knowledge of untrusted regions on the detector. On synthetic data shown, that proposed technique allows to improve tomography reconstruction quality and extends the field of view.