This repository houses a simulated dataset designed for Frequency-domain Diffuse Optical Tomography (FD-DOT) experiments. Each example comprises a target volume representing 3D absorption and reduced scattering properties randomized within a biologically realistic range for breast tissue. Additionally, it includes amplitude and phase components of corresponding frequency-domain reflectance measurements simulated using a high-density grid of source/detector pairs. The dataset encompasses raw data, preprocessed data, mesh information, and supplementary metadata. A detailed description of the dataset structure and contents is provided below.
data/mesh.mat
: The mesh used to generate the data in Matlab using the NIRFAST package.
data/simulated_linescans
: The main dataset.
data/simulated_linescans/dataset_info.json
: Information about the dataset in JSON format.
data/simulated_linescans/measurement_list.csv
: A table containing information on source and detector positions for each SD pair used to generate the data. Each row corresponds to one value in the raw data measurements.
data/simulated_linescans/raw/1.mat
: Raw data for example 1.- Each /mat data file contains the following fields:
amplitude_clean
: Amplitude measurements for each source/detector pair.amplitude_noisy
: Amplitude_clean plus added noise based on a system-derived amplitude-dependent noise model.phase_clean
: Phase measurements for each source/detector pair.phase_noisy
: Phase_clean plus added noise based on a system-derived amplitude-dependent noise model.target
: Ground truth optical properties used to simulate the data. Dimensions represent [x position, y position, z position (depth), optical property (1=mua, 2=mus’)]roi_mask
: Binary mask indicating the presence of anomalies in the target volume. Dimensions represent [x position, y position, z position (depth)]info
: Example-specific information, including the background optical properties, and spatial & contrast details of each anomaly.
- Each /mat data file contains the following fields:
data/simulated_linescans/prepro/prepro_info.json
: Information about the preprocessing procedure used to generate this data.data/simulated_linescans/prepro/train
X.npy
: Preprocessed measurement data in the train split in .numpy format. Dimensions represent [number of examples, number of measurements]Y.npy
: Preprocessed target volume data in the train split in .numpy format. Dimensions represent [number of examples, x position, y position, z position (depth), optical property (1=mua, 2=mus’)]W.npy
: Preprocessed region of interest masks in the train split in .numpy format. Dimensions represent [number of examples, x position, y position, z position (depth)]
data/simulated_linescans/prepro/val
:- Same structure for the validation split.
data/simulated_linescans_testdisks
: Test dataset containing manually designed volumes to test parameter separation and depth sensitivity.- Same structure as
data/simulated_linescans
but also contains:data/simulated_linescans_testdisks/example_list.csv
: Depth and optical property information for each test disk example.
- Same structure as
This dataset was produced as part of a project supported by the National Institute of Biomedical Imaging and Bioengineering (NIBIB) of the National Institutes of Health (NIH) Award Number R01EB029595. Feel free to contact Robin Dale at rbd079@student.bham.ac.uk for any inquiries or additional information.