The Sparse-view Reconstruction Challenge for Four-dimensional Cone-beam CT Dataset

Abstract

The goal of the SPARE challenge was to explore the possibility of high quality 4D CBCT while sparing patients the additional scan time and imaging dose that was currently used in the clinics.

4D CBCT allowed the verification of tumor motion for thoracic patients immediately before every radiotherapy session. A clinical 4D CBCT scan took 2–4 minutes, as compared to one minute for a 3D CBCT scan. The recent emergence of image reconstruction algorithms that accounted for data sparsity offered new possibility for 4D CBCT reconstruction using a shorter scan. Specifically, the ability to reconstruct 4D CBCT images from a one minute scan would have reduced scan time and imaging dose. Additionally, every radiotherapy centre would have gained access to 4D CBCT using existing 3D CBCT scanning protocol. Participants received CBCT projection data either acquired clinically or simulated. Prior CT data and training sets were also be provided. Using these datasets, participants applied their reconstruction algorithms and submitted the final reconstructions to the host within a timeframe of three months. The participants were allowed to apply any processing and algorithms to reconstruct the 4D CBCT images, including scatter correction, projection smoothing, iterative correction, etc.

Together with the reconstruction submission, the participants were asked to include descriptions of the methods they applied. The host evaluated the performance of each algorithm using a set of ground truths that were not available to the participants. The best performing algorithms in terms of image quality and accuracy were identified.