Tumor Tissues FLIM Image Segmentation Dataset: Human Tumors and Xenograft Mouse Models.

<h2 dir="ltr">Dataset Description</h2><p dir="ltr">This dataset contains the data associated with the study <b>"The role of spatial resolution in cellular-scale </b><b>fluorescence lifetime imaging deep-learning </b><b>segmentation of head and neck cancer </b><b>cryosections"</b>, which investigates deep learning-based segmentation of FLIM tumor tissue images using different neural network architectures.</p><p dir="ltr">The dataset includes imaging data from both <b>human tumor samples</b> and <b>xenograft mouse models</b>, together with the corresponding segmentation data and reconstructed images used in the study.</p><h3 dir="ltr">Dataset contents</h3><p dir="ltr">The dataset is organized into the following main categories:</p><ul><li><b>Human tumor data (\human):</b> imaging data and corresponding segmentation data obtained from human tumor samples, each tumor in a separate file.</li><li><b>Xenograft mouse model data (\xenograft):</b> imaging data and corresponding segmentation data obtained from xenograft mouse models, all tumors in the same file.</li><li><b>Reconstructed images (\human_reconstructions; \xenograft_reconstructions) and histopathological stainings (H&E and E-cadherin; \human_histopathological_stainings_and_masks):</b> reconstructed image data and visualization outputs generated as part of the analyses presented in the study.</li><li><b>Metadata:</b> information describing the individual samples, data types, dataset splits, and relevant technical characteristics.</li></ul><p dir="ltr">The numerical data are provided in NumPy (<code>.npy</code>) format.

Detailed information regarding the structure, dimensions, data types, channel ordering, normalization, and interpretation of the individual arrays is provided in the accompanying <code>DATA_DESCRIPTION.md</code> file.</p><h3 dir="ltr">Data organization</h3><p dir="ltr">The dataset distinguishes between human tumor samples and xenograft mouse model samples.</p><p dir="ltr">Each data file is associated with a unique sample identifier.