{"EMPIAR-12885":{"imagesets":[{"segmentations":[],"name":"Test ROI from Dataset 1 used for AIVE benchmarking.","directory":"data/DATASET1_TEST_ROI","category":"micrographs - multiframe","header_format":"TIFF","data_format":"TIFF","num_images_or_tilt_series":1,"frames_per_image":121,"frame_range_min":null,"frame_range_max":null,"voxel_type":"UNSIGNED BYTE","pixel_width":3.2552,"pixel_height":3.2552,"micrographs_file_pattern":"","picked_particles_file_pattern":"","picked_particles_directory":"","details":"Test dataset (cropped from dataset 1) for AIVE benchmarking. Voxel values are inverted from original BSE signal. Spatial units are in nm. 10nm per slice.","image_width":"740","image_height":"370"},{"segmentations":[],"name":"Raw model predictions & AIVE processed data for comparisons between 6 trained models","directory":"data/DATASET1_TEST_ROI/Model_comparisons_-_Membrane_Segmentation","category":"reconstructed volumes","header_format":"TIFF","data_format":"TIFF","num_images_or_tilt_series":12,"frames_per_image":121,"frame_range_min":null,"frame_range_max":null,"voxel_type":"UNSIGNED BYTE","pixel_width":3.2552,"pixel_height":3.2552,"micrographs_file_pattern":"","picked_particles_file_pattern":"","picked_particles_directory":"","details":"All raw membrane predictions and AIVE processed data from Figures 1 & 2 of manuscript, showing direct comparison of results generated via different models. The trained models are RF (Random Forest), J48 (the java compatible extension of Ross Quinlan’s C4.5 classifier), MLP (Multi-Layer Perceptron), DT (Decision Table), JRip (java compatible propositional rule-based RIPPER), and PART (Projective Adaptive Resonance Theory neural network). Slice thickness is 10nm.","image_width":"740","image_height":"370"},{"segmentations":[],"name":"Raw model predictions & human annotations for comparisons after AIVE processing","directory":"data/DATASET1_TEST_ROI/Human_Vs_Unet_-_Mito_Classification","category":"reconstructed volumes","header_format":"TIFF","data_format":"TIFF","num_images_or_tilt_series":9,"frames_per_image":121,"frame_range_min":null,"frame_range_max":null,"voxel_type":"UNSIGNED BYTE","pixel_width":3.2552,"pixel_height":3.2552,"micrographs_file_pattern":"","picked_particles_file_pattern":"","picked_particles_directory":"","details":"Raw annotations and AIVE processed data for mitochondria from Figure 3, using classifications generated by one human on consecutive days, or two U-Nets with 3D anisotropic architecture (different random seeds). \nMembrane predictions by a random forest model, which were used to conduct various forms of AIVE, are also provided.\nSlice thickness is 10nm.","image_width":"740","image_height":"370"},{"segmentations":[{"file":"data/Set1 - AIVE SOURCE DATA/Dataset1_overview - ORGANELLE CLASS LABELS.tif","description":"Organelle classes for Overview Dataset1. Numerical value of each class are identified as follows:\n1=MITOS\n2=LDS\n3=EARLYENDO\n4=GOLGI\n5=LATEENDO\n6=NUC\n7=CYTOSKEL\n8=ER\n9=PLASMEM\n10=VESC","original_files":null,"original_format":"TIFF","entry":null},{"file":"data/Set1 - AIVE SOURCE DATA/Dataset1_overview_MembranePredictions.tif","description":"Raw membrane predictions for Overview Dataset1, as generated by a Random Forest Model. Values are scalars between 0 and 1, indicating the probability of membrane being present at that location.","original_files":null,"original_format":"TIFF","entry":null}],"name":"Overview Dataset 1","directory":"data/Set1_-_AIVE_SOURCE_DATA","category":"micrographs - multiframe","header_format":"TIFF","data_format":"TIFF","num_images_or_tilt_series":1,"frames_per_image":724,"frame_range_min":null,"frame_range_max":null,"voxel_type":"UNSIGNED BYTE","pixel_width":6.5104,"pixel_height":6.5104,"micrographs_file_pattern":"","picked_particles_file_pattern":"","picked_particles_directory":"","details":"Tiff stack for half-scale overview FIB-SEM dataset 1. Slice thickness is 10nm.","image_width":"2960","image_height":"720"},{"segmentations":[{"file":"data/Set2 - AIVE SOURCE DATA/Dataset2_overview - ORGANELLE CLASS LABELS.tif","description":"Organelle classes for Overview Dataset2. Numerical value of each class are identified as follows:\n1=NUC\n2=MITOS\n3=LDS\n4=PLASMEM\n5=CHROMATIN\n6=ER\n7=CYTOSKEL\n8=LATEENDO\n9=EARLYENDO\n10=VESC","original_files":null,"original_format":"TIFF","entry":null},{"file":"data/Set2 - AIVE SOURCE DATA/Dataset2_overview_MembranePredictions.tif","description":"Raw membrane predictions for Overview Dataset2, as generated by a Random Forest Model. Values are scalars between 0 and 1, indicating the probability of membrane being present at that location.","original_files":null,"original_format":"TIFF","entry":null}],"name":"Overview Dataset 2","directory":"data/Set2_-_AIVE_SOURCE_DATA","category":"micrographs - multiframe","header_format":"TIFF","data_format":"TIFF","num_images_or_tilt_series":1,"frames_per_image":858,"frame_range_min":null,"frame_range_max":null,"voxel_type":"UNSIGNED BYTE","pixel_width":6.5104,"pixel_height":6.5104,"micrographs_file_pattern":"","picked_particles_file_pattern":"","picked_particles_directory":"","details":"Tiff stack for half-scale overview FIB-SEM dataset 2. Slice thickness is 10nm.","image_width":"2930","image_height":"806"},{"segmentations":[{"file":"data/Set3 - AIVE SOURCE DATA/Dataset3_overview - ORGANELLE CLASS LABELS.tif","description":"Organelle classes for Overview Dataset3. Numerical value of each class are identified as follows:\n1=MITOS\n2=LDS\n3=LATEENDOS\n4=EARLYENDOS\n5=NUC\n6=CYTOSKEL\n7=GOLGI\n8=ER\n9=PLASMEM\n10=VESC","original_files":null,"original_format":"TIFF","entry":null},{"file":"data/Set3 - AIVE SOURCE DATA/Dataset3_overview_MembranePredictions.tif","description":"Raw membrane predictions for Overview Dataset3, as generated by a Random Forest Model. Values are scalars between 0 and 1, indicating the probability of membrane being present at that location.","original_files":null,"original_format":"TIFF","entry":null}],"name":"Overview Dataset 3","directory":"data/Set3_-_AIVE_SOURCE_DATA","category":"micrographs - multiframe","header_format":"TIFF","data_format":"TIFF","num_images_or_tilt_series":1,"frames_per_image":618,"frame_range_min":null,"frame_range_max":null,"voxel_type":"UNSIGNED BYTE","pixel_width":6.5104,"pixel_height":6.5104,"micrographs_file_pattern":"","picked_particles_file_pattern":"","picked_particles_directory":"","details":"Tiff stack for half-scale overview FIB-SEM dataset 3. Slice thickness is 10nm.","image_width":"2948","image_height":"830"},{"segmentations":[{"file":"data/Set4 - AIVE SOURCE DATA/Dataset4_MitoClasss.tif","description":"Mitochondrial class for muscle tissue overview.","original_files":null,"original_format":"TIFF","entry":null},{"file":"data/Dataset4_overview_MembranePredictions.tif","description":"Raw membrane predictions for Overview Dataset3, as generated by a Random Forest Model. Values are scalars between 0 and 1, indicating the probability of membrane being present at that location.","original_files":null,"original_format":"TIFF","entry":null}],"name":"Overview Dataset 4 - Muscle","directory":"data/Set4_-_AIVE_OUTPUTS","category":"micrographs - multiframe","header_format":"TIFF","data_format":"TIFF","num_images_or_tilt_series":1,"frames_per_image":311,"frame_range_min":null,"frame_range_max":null,"voxel_type":"UNSIGNED BYTE","pixel_width":16.0,"pixel_height":16.0,"micrographs_file_pattern":"","picked_particles_file_pattern":"","picked_particles_directory":"","details":"Tiff stack for muscle tissue. Slice thickness is 20nm.","image_width":"500","image_height":"500"}],"workflow_file":null,"grant_references":[],"version_history":[],"title":"Source data for AI-directed voxel extraction and volume EM identify intrusions as sites of mitochondrial contact","principal_investigator":[{"author_orcid":"0000-0003-2150-5545","middle_name":null,"organization":"Walter and Eliza Hall Institute","street":"Elizabeth Street","town_or_city":"Parkville","state_or_province":"Victoria","post_or_zip":"3000","telephone":null,"fax":null,"first_name":"Michael","last_name":"Lazarou","email":"lazarou.m [at] wehi.edu.au","country":"Australia","entry":"EMPIAR-12885"}],"status":"REL","deposition_date":"2025-02-21","release_date":"2025-11-25","obsolete_date":null,"update_date":"2025-11-25","corresponding_author":{"author":{"author_orcid":"0000-0002-5710-6100","middle_name":"Scott","organization":"The Kids Institute & University of Western Australia, Nedlands, Western Australia, Australia.","street":"Stirling Hwy","town_or_city":"Perth","state_or_province":"Western Australia","post_or_zip":"6009","first_name":"Benjamin","last_name":"Padman","country":"Australia"}},"authors":[{"author":{"name":"Padman BS","author_orcid":"0000-0002-5710-6100"}},{"author":{"name":"Lindblom R","author_orcid":"0000-0001-6755-8744"}},{"author":{"name":"Lazarou M","author_orcid":"0000-0003-2150-5545"}}],"cross_references":[],"biostudies_references":[],"idr_references":[],"empiar_references":[],"citation":[{"authors":[{"name":"Padman BS","author_orcid":"0000-0002-5710-6100"},{"name":"Lindblom R","author_orcid":"0000-0001-6755-8744"},{"name":"Lazarou M","author_orcid":"0000-0003-2150-5545"}],"editors":[],"published":true,"j_or_nj_citation":true,"title":"AI-directed voxel extraction and volume EM identify intrusions as sites of mitochondrial contact","volume":null,"country":"","first_page":null,"last_page":null,"year":"2024","language":null,"doi":"10.1083/jcb.202411138","pubmedid":null,"details":"Source data and segmentation generated for \"AI-directed voxel extraction and volume EM identify intrusions as sites of mitochondrial contact\"","book_chapter_title":null,"publisher":null,"publication_location":null,"journal":"bioRxiv","journal_abbreviation":"","issue":null,"preprint":true}],"dataset_size":"32.8 GB","experiment_type":"FIB-SEM","scale":"cell","entry_doi":"10.6019/EMPIAR-12885"}}