1 research outputs found
The LoDoPaB-CT Dataset: A Benchmark Dataset for Low-Dose CT Reconstruction Methods
Deep Learning approaches for solving Inverse Problems in imaging have become
very effective and are demonstrated to be quite competitive in the field.
Comparing these approaches is a challenging task since they highly rely on the
data and the setup that is used for training. We provide a public dataset of
computed tomography images and simulated low-dose measurements suitable for
training this kind of methods. With the LoDoPaB-CT Dataset we aim to create a
benchmark that allows for a fair comparison. It contains over 40,000 scan
slices from around 800 patients selected from the LIDC/IDRI Database. In this
paper we describe how we processed the original slices and how we simulated the
measurements. We also include first baseline results