Magnetic Particle Imaging X-Space Reconstruction Data

This dataset supports a convex formulation for 3D Magnetic Particle Imaging (MPI) x-space reconstruction, addressing prior limitations of 1D approaches. It was created by Justin J. Konkle and published in 2020 under a CC0 license. The dataset is associated with research on reducing non-physical banding and haze artifacts in MPI.

Use Cases

• Apply convex optimization methods to 3D MPI x-space reconstruction data to reduce banding artifacts.
• Benchmark image reconstruction algorithms using data from rat-sized fields of view for MPI applications.
• Analyze the impact of signal filtering on zero-frequency value recovery in MPI reconstruction workflows.
• Validate a priori knowledge of image smoothness and non-negativity constraints on MPI reconstruction data.

Strengths

• Dataset is associated with a published methodological advancement for 3D MPI reconstruction.
• Data supports research in multiple clinical applications including angiography and cancer imaging.
• Released under a permissive CC0 1.0 public domain dedication license.

Limitations

• The specific data structure, including column names, row count, and file formats, is unknown.
• The dataset's size and sample data are unavailable, limiting assessment of its analytical scope.
• Data is from 2020 and may not reflect the most recent advancements in MPI technology.

Provenance

Source

dryad

Collection Method

Data associated with a research paper on MPI x-space reconstruction.

Freshness

Last updated on 2020-06-24.