Arctique - Review version

This is the review version of the dataset introduced in the NeurIPS 2024 submission "Arctique: An Artificial Histopathological Dataset Unifying Realism and Controllability for Uncertainty Quantification." It contains 3,426 images along with their corresponding instance and semantic masks. The full dataset, comprising 50,000 images and masks, will be published upon acceptance. The Arctique dataset is split into training and test sets and variations, each containing the following directories: The images directory contains all synthetically generated images stored as PNG files. Each image has a resolution of 512x512 pixels with RGB channels and is named "img_<ID>", where <ID> is a unique integer identifier for each image. The masks directory includes subdirectories containing various masks related to the images. Note that all semantic masks appear as black images when viewed with a standard image viewer. This is because the cell type IDs, ranging from 1 to 6, are used as greyscale values, which appear dark in the images. cytoplasm: Contains 2D semantic masks for the cell cytoplasm. Each mask corresponds to an image named "<ID>.tif", where "<ID>" is the identifier for that image. The mask file is named using the same identifier. instance_3d: Contains a directory for each image, named "<ID>. Inside each directory, there is a 3D stack numpy file representing the instance IDs in a 3D volumetric array. Additionally, it includes a sequence of 2D instance segmentation masks, named "slice_<ID>_<slice_count>.png", each representing equidistant slices through the 3D volume along the depth axis. instance: Contains 2D instance masks for the cell nuclei. Each mask corresponds to an image named "<ID>.tif", and the mask file is named with the same identifier. semantic: Contains 2D semantic masks for the cell nuclei. Similar to the instance masks, each mask corresponds to an image named "<ID>.tif", with the mask file named using the same identifier. The metadata directory contains JSON metadata files named "metadata_<ID>" for each image. Each JSON file includes a list of Python dictionaries, one for each cell object visible in the image. Consider submission appendix F for a detailed explanation of each dictionary. The parameters directory contains JSON files named "parameters_<ID>", which detail the parameters used to generate each image. Each JSON file is a Python dictionary with all the parameter values necessary to reproduce the scene. Consider submission appendix F for a detailed explanation of each parameter.