Original data of manuscript entitled "Spatial quantification of clinical biomarker pharmacokinetics through deep learning-based segmentation and signal-oriented analysis of MSOT data" by Hoffmann and Gerst et al.

This dataset contains all original data used in the manuscript entitled "Spatial quantification of clinical biomarker pharmacokinetics through deep learning-based segmentation and signal-oriented analysis of MSOT data" by Hoffmann and Gerst <i>et al</i>.<br><br>Contained data:<br><br>1. Anatomical_RoiSets.zip<br>This folder contains anatomical ROI sets of liver, spine and aorta regions used in the manuscript.<br>2. Annotation-comparison_ROIs.zipThis folder contains all ROI sets used for the comparison of manual and automated annotation.<br>3. Deep-learning_manual-annotation_data.zipThis folder contains the manual annotations used for the deep learning-based segmentation of animals.<br>4. Deep-learning_training.zipThis folder contains the the code and data used for training of the deep learning-based segmentation of MSOT images.<br>5. Signal-oriented_analysis_data.zip<br>This folder contains all data used for the signal-oriented analysis.<br>The data consists of two different treatments: Sham (control animals) and PCI (diseased animals). Each animal folder is identified by a unique name and contains an MSOT image in .tif file format and a region of interest (ROI) in .roi file format. The MSOT image is a time-resolved 4d image with 4 channels (water, indocyanine green, deoxygenated haemoglobin and oxygenated haemoglobin). The ROI derived by deep learning-based segmentation comprises the whole animal and is referred to as animal-ROI in the manuscript.<br><br>6. Tissue-oriented_analysis_data.zip<br>This folder contains all data used for the tissue-oriented analysis.<br>The data consists of two different treatments: Sham (control animals) and PCI (diseased animals). For each animal there exist two files prefixed with the animal identifier: a pre-processed MSOT image in .tif file format and a region of interest (ROI) in .roi file format. The MSOT image is a pre-processed, time-resolved 3d image of the indocyanine green channel (see manuscript for details on image pre-processing). The ROI comprises the liver tissue and is The third folder contains the MSOT image and the ROIs that were used to demonstrate the sensitivity of the tissue-oriented analysis towards slight changes in ROI positioning.<br><br>