2DeteCT - A large 2D expandable, trainable, experimental Computed Tomography dataset for machine learning.

ABSTRACT: Recent research in computational imaging largely focuses on developing machine learning (ML) techniques for image reconstruction, which requires large-scale training datasets consisting of measurement data and ground-truth images. However, suitable experimental datasets for X-ray Computed Tomography (CT) are scarce, and methods are often developed and evaluated only on simulated data. We fill this gap by providing the community with a versatile, open 2D fan-beam CT dataset suitable for developing ML techniques for a range of image reconstruction tasks. To acquire it, we designed a sophisticated, semi-automatic scan procedure that utilizes a highly-flexible laboratory X-ray CT setup. A diverse mix of samples with high natural variability in shape and density was scanned slice-by-slice (5,00

SUBMITTER: Kiss MB 

PROVIDER: S-EPMC10477177 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature