arXiv subjects

Edward Robert Criscuolo

Publications and source records attributed to Edward Robert Criscuolo.

2 recordsLinked to original sources

arXiv2026

Develop and Optimize 5DCT Imaging Simulation and Reconstruction Methods

Purpose: To develop and optimize a 5DCT (3D + cardiac phase + respiratory phase) imaging simulation and reconstruction pipeline, and to compare two sinogram-space interpolation methods for reconstructing images at arbitrary combinations of cardiac and respiratory phase. Methods: Helical CT projections were simulated from the 4D XCAT phantom across a range of cardiac and respiratory motion states, with Poisson and electronic noise added. Ground-truth-matched volumes were generated at 5 cardiac phases and 10 respiratory amplitudes (50 total phase combinations). Because acquired projections are sparsely and unevenly distributed across this joint phase space, each target slice was reconstructed by interpolating rebinned sinogram rows to the target cardiac phase and respiratory amplitude, using either 2D scattered barycentric interpolation or 2D scattered local linear interpolation with a circular kernel for cardiac phase. Reconstructed volumes were compared to phantom ground truth using mean absolute error (MAE), and to conventional respiratory-gated 4DCT (r4DCT) reconstructed from the same simulated data. Results: Both interpolation methods eliminated the severe axial misalignment artifacts present when helical projections were reconstructed without phase-space interpolation. Local linear interpolation achieved lower MAE than barycentric interpolation across most tested conditions, with the largest improvement at low pitch. The 5DCT pipeline also produced respiratory-only volumes with fewer residual cardiac-motion artifacts than conventional r4DCT reconstructed from the same projection data, including at standard clinical pitch (0.1). Conclusions: 5DCT reconstruction using sinogram-space interpolation is feasible and can jointly resolve cardiac and respiratory motion with better accuracy than conventional 4DCT reconstruction.

physics.med-ph↗

arXiv2024

A comprehensive liver CT landmark pair dataset for evaluating deformable image registration algorithms

Purpose: Evaluating deformable image registration (DIR) algorithms is vital for enhancing algorithm performance and gaining clinical acceptance. However, there's a notable lack of dependable DIR benchmark datasets for assessing DIR performance except for lung images. To address this gap, we aim to introduce our comprehensive liver computed tomography (CT) DIR landmark dataset library. Acquisition and Validation Methods: Thirty CT liver image pairs were acquired from several publicly available image archives as well as authors' institutions under institutional review board approval. The images were processed with a semi-automatic procedure to generate landmark pairs: 1) for each case, liver vessels were automatically segmented on one image; 2) landmarks were automatically detected at vessel bifurcations; 3) corresponding landmarks in the second image were placed using the deformable image registration method; 4) manual validation was applied to reject outliers and confirm the landmarks' positional accuracy. This workflow resulted in an average of ~68 landmark pairs per image pair, in a total of 2028 landmarks for all 30 cases. The general landmarking accuracy of this procedure was evaluated using digital phantoms. Estimates of the mean and standard deviation of landmark pair target registration errors (TRE) on digital phantoms were 0.64 and 0.40 mm. 99% of landmark pairs had TREs below 2 mm. Data Format and Usage Notes: All data are publicly available at Zenodo. Instructions for using our data and MATLAB code can be found on our GitHub page. Potential Applications: The landmark dataset generated in this work is the first collection of large-scale liver CT DIR landmarks prepared on real patient images. This dataset can provide researchers with a dense set of ground truth benchmarks for the quantitative evaluation of DIR algorithms within the liver.

physics.med-ph↗