A recent paper published in Physics in Medicine and Biology by Hao Dang and coauthors in the I-STAR Lab reports a multi-resolution CT image reconstruction method that efficiently overcomes truncation effects, which are a particularly important problem in cone-beam CT (which often has limited field of view) and can confound iterative model-based image reconstruction (MBIR) methods.
Data truncation in CBCT results in artifacts that reduce image uniformity and challenge reliable diagnosis. For a recently developed prototype CBCT head scanner, truncation of the head and/or head holder can hinder the detection of intracranial hemorrhage (ICH).
The multi-resolution method is based on a similar approach shown by Qian Cao and coauthors for orthopaedic imaging, which allows simultaneous high-resolution reconstruction of bone regions and lower-resolution (lower-noise) reconstruction of surrounding soft tissue. In Hao Dang’s paper, a similar concept is used to overcome truncation artifacts by performing a high-resolution reconstruction of the interior with a lower-resolution reconstruction outside the RFOV.
The algorithm was tested in experiments involving CBCT of the head with truncation due to a carbon-fiber head support. Conventional (single-resolution) MBIR, showed severe artifacts and poor convergence properties, and the proposed method with a multi-resolution extension of the RFOV minimized truncation artifacts. Compared to brute-force reconstruction of the larger RFOV, the multi-resolution approach reduced computation time by as much as 95% (for an image volume up to 10003 voxels).
The findings provide a promising method for minimizing truncation artifacts in CBCT and may be useful for MBIR methods in general, which can be confounded by truncation effects.
Read the full paper in Phys Med Biol here.