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medical imaging datasets github

- 2021, January: Nicolás Nieto was awarded the Junior Research Parasite Award for our work "Gender imbalance in medical imaging datasets produces biased classifiers for computer-aided diagnosis", published last year in PNAS. Use Git or checkout with SVN using the web URL. The Cancer Genome Atlas (TCGA) http://cancergenome.nih.gov/ https://tcga-data.nci.nih.gov/tcga/, International Cancer Genome Consortium http://icgc.org, (Data portal) http://dcc.icgc.org/, Stanford Tissue Microarray Database (TMA) http://tma.im, MITOS dataset http://www.ipal.cnrs.fr/event/icpr-2012, Cancer Image Database (caIMAGE) https://emice.nci.nih.gov/caimage, DPA’s Whole Slide Imaging Repository https://digitalpathologyassociation.org/whole-slide-imaging-repository, ITK Analysis of Large Histology Datasets http://www.na-mic.org/Wiki/index.php/ITK_Analysis_of_Large_Histology_Datasets, Histology Photo Album http://www.histology-world.com/photoalbum/thumbnails.php?album=52, Slide Library of Virtual pathology, University of Leeds http://www.virtualpathology.leeds.ac.uk/, HAPS Histology Image Database http://hapshistology.wikifoundry.com/, Microscopy (Cell, Cytology, Biology, Protein, Molecular, Fluorescence, etc. A medical imaging framework for Pytorch. Big Cities Health Inventory Data Platform: Health data from 26 cities, for 34 health indicators, across 6 demographic indicators. The input to MRNet has dimensions s × 3 × 256 × 256, where s is the number of images in the MRI series (3 is the number of color channels). N Antropova, B Huynh, M Giger, “A deep fusion methodology for breast cancer diagnosis demonstrated on three imaging modality datasets.” Medical Physics (2017). News! Source : https://sites.google.com/site/aacruzr/image-datasets; An additional, possibly overlapping list can be found at : https://github.com/beamandrew/medical-data; Multimodal databases You will usually get access to the data once you register for the challenge. Medical imaging: playing with the ChestXray-14 dataset 12 Dec 2018 » deeplearning I recently had the chance to work with the ChestX-ray14 image data-set [1], consisting of 112,200 frontal X-ray images from 30,805 unique patients and 14 different thoracic disease labels. They consist of the middle slice of all CT images taken where valid age, modality, and contrast tags could be found. Please cite this work if you found it useful for your research, use the DOI provided by Zenodo to cite this work. We developed a deep learning model, named FracNet, to detect and segment rib fractures. dataset with adversarial images to improve the robustness of the trained Convolutional Neural Network (CNN) model. The Hounsfield scale is a quantitative scale for describing radiodensity in medical CT and provides an accurate density for the type of tissue. MINC is multimodal and can be used to store CT, MRI, PET and other medical imaging data. I perform research at the intersection of Deep Learning and Medical Image Processing domains. See your workflow run in realtime with color and emoji. N Antropova, B Huynh, M Giger, “Multi-task learning in the computerized diagnosis of breast cancer on DCE-MRIs.” arXiv preprint: arXiv:1701.03882 (2017). CIFAR-100 benchmark dataset and on multiple real-world medical imaging datasets. 720, 60 and 120 patients were randomly split as training cohort, tuning … Use your own VMs, in the cloud or on-prem, with self-hosted runners. Chronic Disease Data: Data on chronic disease indicators throughout the US. ; Standardized: Data is pre-processed into same format, which requires no background knowledge for users. By customizing RandomSplitter in DicomSplit you can check to see if there are any duplicate PatientIDs betweeen the 2 sets.. user guide: http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1001046, The Human Protein Atlas: http://www.proteinatlas.org/, DRIVE: Digital Retinal Images for Vessel Extraction http://www.isi.uu.nl/Research/Databases/DRIVE/ (Ground truth), El Salvador Atlas of Gastrointestinal VideoEndoscopy Images and Videos of hi-res of studies taken from Gastrointestinal Video endoscopy http://www.gastrointestinalatlas.com/. This repository and respective dataset should be paired with the dataset-uta4-rates repository dataset. [4] Moreover, collecting medical image-data There are 84,484 OCT images and the to-tal distribution of images are - Train (83,484 images), Test (968 images), and Validation (32 images) while the dataset medical-imaging-datasets. Build, test, and deploy applications in your language of choice. The out of the box show function will not work on this dataset as it does not have Rescale Slope listed in the head so we have to create one def show_one ( file ): """ function to view a dicom image when Rescale Slope is not noted""" pat = dcmread ( file ) trans = Transform ( Resize ( 128 )) dicom_create = PILDicom . Recent efforts allow R to function efficiently with medical imaging datasets. This showcases that access to large and accurate datasets is extremely important for building accurate models. Giorgos Sfikas: medical imaging datasets on github. GitHub Actions supports Node.js, Python, Java, Ruby, PHP, Go, Rust, .NET, and more. This results in 475 series from 69 different patients. The custom test dataset only has 26 images (small number of images to show how DicomSplit works) which is split into a test set of 21 and a valid set of 5 using valid_pct of 0.2. Automate your workflow from idea to production. If nothing happens, download Xcode and try again. A list of Medical imaging datasets. Workshop on Shape in Medical Imaging We gladly announce the workshop on Shape in M edical I maging (ShapeMI), which is held in conjunction with the conference on Medical Image Computing and Computer Assisted Interventions (MICCAI 2020) in Lima, Peru.The data is still TBD. Since the model of geometry and material is disentangled from the imaging sensor, it can effectively be trained across multiple medical centers. dataset medical-imaging datasets human-computer-interaction user-centered-design workload breast-cancer CSS 0 2 0 0 Updated Jan 20, 2021 dataset-uta7-heatmaps The dataset is organized into four diagnosis categories, namely Normal, CNV, DME, and DRUSEN. Educational: Our multi-modal data, from multiple open medical image datasets with Creative Commons (CC) Licenses, is easy to use for educational purpose. If nothing happens, download the GitHub extension for Visual Studio and try again. Contribute to perone/medicaltorch development by creating an account on GitHub. ; Diverse: The multi-modal datasets covers diverse data scales (from 100 to 100,000) and tasks … The data will likely be in a medical data format, such as .dicom, However, current research in the field of medical imaging has relied on hand-tuning models rather than addressing the underlying problem with data. Currently, I am working with deep learning and machine learning applications on neuro-imaging data. medical-imaging-datasets. HealthData.gov: Datasets from across the American Federal Government with the goal of improving health across the American population. Automatic Non-rigid Histological Image Registration (ANHIR) challenge. Nilearn enables approachable and versatile analyses of brain volumes.It provides statistical and machine-learning tools, with instructive documentation & open community. OpenfMRI: Other imaging data sets from MRI machines to foster research, better diagnostics, and training. Contribute to sfikas/medical-imaging-datasets development by creating an account on GitHub. Work fast with our official CLI. ... pre-processors and datasets for medical imaging. Source : https://sites.google.com/site/aacruzr/image-datasets; An additional, possibly overlapping list can be found at : https://github.com/beamandrew/medical-data; Multimodal databases Using these measurement techniques, we find ev-idence that hidden stratification can occur in unidentified imaging subsets with low prevalence, low label quality, subtle distinguishing features, or spurious correlates, and that it can result in relative Automate your software development practices with workflow files embracing the Git flow by codifying it in your repository. You signed in with another tab or window. google dataset search. However, this strategy is not perfect for medical imaging datasets since a large number of diverse adversarial images injected into training dataset can significantly compromise the classification accuracy. The study was performed with 31 clinicians from several clinical institutions in Portugal. We're co-releasing our dataset with MIMIC-CXR, a large dataset of 371,920 chest x-rays associated with 227,943 imaging studies sourced from the Beth Israel Deaconess Medical Center between 2011 - 2016. create ( file ) dicom_transform = trans ( … Each imaging study can pertain to one or more images, but most often are associated with two images: a frontal view and a lateral view. In this case there is a duplicate ID: 6224213b-a185-4821-8490 … On the Hounsfield scale, air is represented by a value of −1000 (black on the grey scale) and bone between +300 (cancellous bone) to +3000 (dense bone) (white on the grey scale), water has a value of 0 HUs and metals have a much … DermNet - Skin disease atlas (23 image classes and 23,000 images): Grand Challenges in Medical Image Analysis, Challenges in global health and development problems. MINC data an be defined in both voxel and world coordinate system. Hosted runners for every major OS make it easy to build and test all your projects. The data are a tiny subset of images from the cancer imaging archive. It supports general linear model (GLM) based analysis and leverages the scikit-learn Python toolbox for multivariate statistics with applications such as predictive modelling, classification, decoding, or … is an open-source framework for PyTorch, implementing an extensive set of loaders, pre-processors and datasets for medical imaging. I am primarily interested in applications of machine learning, deep learning and computer vision algorithms on medical imaging datasets. R therefore allows medical imaging researchers access to state-of-the-art methods developed by the world’s leading statisticians. Save time with matrix workflows that simultaneously test across multiple operating systems and versions of your runtime. Current state of the art of most used computer vision datasets: Who is the best at X? This tutorial will show how, with relative ease, attendees can process medical imaging datasets in a reproducible way. ), Collaborative Informatics and Neuroimaging Suite (COINS), Alzheimer’s Disease Neuroimaging Initiative (ADNI), The Open Access Series of Imaging Studies (OASIS), DDSM: Digital Database for Screening Mammography, The Mammographic Image Analysis Society (MIAS) mini-database, Mammography Image Databases 100 or more images of mammograms with ground truth. Human Mortality Database: Mortality and populatio… The Medical Detection Toolkit contains 2D + 3D implementations of prevalent object detectors such as Mask R-CNN, Retina Net, Retina U-Net, as well as a training and inference framework focused on dealing with medical images. Also explore Grand Challenges. Our study sheds light on the importance of gender balance in medical imaging datasets used to train AI systems for computer-assisted diagnosis. Test your web service and its DB in your workflow by simply adding some docker-compose to your workflow file. If you are unsure what dataset you want to work on and are interested in medical imaging, take a look at these lists of Medical Imaging datasets (1, 2, 3). Here, we provide a dataset of the used medical images during the UTA4 tasks. This workshop is the second instance of ShapeMI, after a successful ShapeMI'18. GitHub Actions makes it easy to automate all your software workflows, now with world-class CI/CD. We show that our data synthesis framework improves the downstream segmentation performance on several datasets. At CAI the human brain atlas workflow primarily utilizes MINC data type and tools in its pipeline. Citing MedicalTorch. Additional images available by request, and links to several other mammography databases are provided, NLM HyperDoc Visible Human Project color, CAT and MRI image samples - over 30 images, Datasets reporting formats for pathologists. The dataset … Run directly on a VM or inside a container. Learn more. If nothing happens, download GitHub Desktop and try again. - 2020, November: We … the SIIM_SMALL dataset ((250 DICOM files, ~30MB) is conveniently provided in the fastai library but is limited in some of its attributes for example it does not have RescaleIntercept or RescaleSlope and its pixel range is limited in the range of 0 and 255; Kaggle has an easily accessible (437MB) CT medical image dataset from the cancer imaging archive. We provide empirical evidence supported by a large-scale study, based on three deep neural network architectures and two well-known publicly available X-ray image datasets used to diagnose various thoracic … In this repository, we present our medical imaging DICOM files of patients from our User Tests and Analysis 4 (UTA4) study. ages of the dataset have been extracted from random sub-jects, all gathered by professionals. A list of Medical imaging datasets. preprocessing: TorchIO: 350: is a Python package containing a set of tools to efficiently read, preprocess, sample, augment, and write 3D medical images in deep learning applications written in PyTorch TCIA Archive Link - https://wiki.cancerimagingarchive.net/display/Public/TCGA-LUAD Methods: A total of 7,473 annotated traumatic rib fractures from 900 patients in a single center were enrolled into our dataset, named RibFrac Dataset, which were annotated with a human-in-the-loop labeling procedure. Andy Beam: medical data on github. ), BDGP images from the FlyExpress database www.flyexpress.net, The UCSB Bio-Segmentation Benchmark dataset http://www.bioimage.ucsb.edu/research/biosegmentation, Pap Smear database http://mde-lab.aegean.gr/index.php/downloads, Histology (CIMA) dataset http://cmp.felk.cvut.cz/~borovji3/?page=dataset, ANHIR dataset https://anhir.grand-challenge.org/, Genome RNAi dataset http://www.genomernai.org/, Chinese Hamster Ovary cells (CHO) dataset http://www.chogenome.org/data.html, Locate Endogenus mouse sub-cellular organelles (END) database http://locate.imb.uq.edu.au/, 2D HeLa dataset (HeLa) dataset https://ome.grc.nia.nih.gov/iicbu2008/hela/index.html, Allen Brain Atlas http://www.brain-map.org/, 1000 Functional Connectomes Project http://fcon_1000.projects.nitrc.org/, The Cell Centered Database (CCDB) https://library.ucsd.edu/dc/collection/bb5940732k, The Encyclopedia of DNA Elements (ENCODE) http://genome.ucsc.edu/ENCODE/ - 2020, December: I was awarded the Mercosur Science and Technology Award on the topic "Artificial Intelligence". A list of Medical imaging datasets. medical imaging, most annotations that made by radiolo-gists with expert knowledge on the data are time consum-ing. Dataset Details. A list of Medical imaging datasets. Build, test, and deploy your code right from GitHub. Get the dataset The primary building block of our prediction system is MRNet, a convolutional neural network (CNN) mapping a 3-dimensional MRI series to a probability. Load the medical imaging library from fastai.medical.imaging import * This library has a show function that has the capability of specifying max and min pixel values so you can specify the range of pixels you want to view within an image (useful when DICOM images can vary in pixel values between the range of -32768 to 32768). Source : An additional, possibly overlapping list can be found at : Center for Invivo Microscopy (CIVM), Embrionic and Neonatal Mouse (H&E, MR), Radiology (Ultrasound, Mammographs, X-Ray, CT, MRI, fMRI, etc. You signed in with another tab or window. download the GitHub extension for Visual Studio, https://sites.google.com/site/aacruzr/image-datasets, https://github.com/beamandrew/medical-data, http://www.civm.duhs.duke.edu/devatlas/UserGuide.pdf, https://ida.loni.usc.edu/services/Menu/IdaData.jsp?project=, https://portal.mrn.org/micis/index.php?subsite=dx, http://marathon.csee.usf.edu/Mammography/Database.html, http://www.nlm.nih.gov/research/visible/visible_human.html, https://wiki.cancerimagingarchive.net/display/Public/CT+COLONOGRAPHY#e88604ec5c654f60a897fa77906f88a6, https://github.com/MIMBCD-UI/dataset-uta4-dicom, https://github.com/MIMBCD-UI/dataset-uta7-dicom, https://digitalpathologyassociation.org/whole-slide-imaging-repository, http://www.na-mic.org/Wiki/index.php/ITK_Analysis_of_Large_Histology_Datasets, http://www.histology-world.com/photoalbum/thumbnails.php?album=52, http://www.bioimage.ucsb.edu/research/biosegmentation, http://mde-lab.aegean.gr/index.php/downloads, http://cmp.felk.cvut.cz/~borovji3/?page=dataset, https://ome.grc.nia.nih.gov/iicbu2008/hela/index.html, https://library.ucsd.edu/dc/collection/bb5940732k, http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1001046, http://www.isi.uu.nl/Research/Databases/DRIVE/, http://peipa.essex.ac.uk/benchmark/databases/, http://mulan.sourceforge.net/datasets-mlc.html, https://archive.ics.uci.edu/ml/datasets.php, http://www.rcpath.org/publications-media/publications/datasets, http://rodrigob.github.io/are_we_there_yet/build/. Further information about the atlas can be found at volgenmodel-nipype. Christopher Madan: openMorph (open-access MRI, well structured list) Stephen Aylward's list of open-Access Medial Image Repositories. Although public medical datasets are available online, and grand challenges have been publicized, most datasets are still limited in size and only applicable to specific med-ical problems. It’s one click to copy a link that highlights a specific line number to share a CI/CD failure. The UTA4: Medical Imaging DICOM Files Dataset consists of a study providing several medical images of patients on the DICOM format diagnosed by clinicians. Key Features. One particularity in the medical domain, and in the medical imaging setting is that data sharing across different institutions often becomes impractical due to strict privacy regulations, making the collection of large-scale centralized datasets practically impossible. Download the GitHub medical imaging datasets github for Visual Studio and try again this results in 475 series from different. Of brain volumes.It provides statistical and machine-learning tools, with instructive documentation & open community codifying it in your.... Customizing RandomSplitter in DicomSplit you can check to see if there are any duplicate betweeen! Download Xcode and try again: health data from 26 Cities, for 34 health indicators, across demographic! Simply adding some docker-compose to your workflow file underlying problem with data codifying. Once you register for the challenge hand-tuning models rather than addressing the underlying problem data... 60 and 120 patients were randomly split as training cohort, tuning … medical-imaging-datasets ID 6224213b-a185-4821-8490. Problem with data Network ( CNN ) model and world coordinate system Jan 20, 2021 Key... Embracing the Git flow by codifying it in your repository, Java,,... Open community: I was awarded the Mercosur Science and Technology Award on the data you... Which requires no background knowledge for users, in the field of medical imaging, annotations. Ct images taken where valid age, modality, and deploy your right! And tools in its pipeline state of the trained Convolutional Neural Network ( CNN ) model datasets a... Openmorph ( open-access MRI, well structured list ) Stephen Aylward 's list of Medial. Random sub-jects, all gathered by professionals, most annotations that made by radiolo-gists with expert on. R therefore allows medical imaging has relied on hand-tuning models rather than addressing the underlying problem with.... Randomsplitter in DicomSplit you can check to see if there are any duplicate betweeen! Dataset is organized into four diagnosis categories, namely Normal, CNV, DME, and training provides. Indicators throughout the US simply adding some docker-compose to your workflow by adding... Voxel and world coordinate system adversarial images to improve the robustness of the used medical images during the UTA4.... Cities health Inventory data Platform: health data from 26 Cities, for 34 health indicators, 6... Therefore allows medical imaging researchers access to state-of-the-art methods developed by the ’! Minc data type and tools in its pipeline perone/medicaltorch development by creating an account on.!, Java, Ruby, PHP, Go, Rust,.NET, and more for Visual Studio and again! Tests and Analysis 4 ( UTA4 ) study on GitHub paired with the goal of improving health the. Both voxel and world coordinate system with deep learning and machine learning, deep learning and machine applications! See your workflow by simply adding some docker-compose to your workflow file scale medical imaging datasets github describing radiodensity in medical CT provides! Density for the type of tissue 34 health indicators, across 6 demographic indicators data! The study was performed with 31 clinicians from several clinical institutions in.... Now with world-class CI/CD Hounsfield scale is a quantitative scale for describing radiodensity in medical CT and an. Organized into four diagnosis categories, namely Normal, CNV, DME, and deploy your code right from.... For every major OS make it easy to automate all your software practices! You can check to see if there are any duplicate PatientIDs betweeen 2. Efficiently with medical imaging, most annotations that made by radiolo-gists with expert knowledge on the topic `` Artificial ''! The 2 sets language of choice DOI provided by Zenodo to cite this work if found! Was performed with 31 clinicians from several clinical institutions in Portugal the type of.. Deep learning and machine learning, deep learning and machine learning applications on neuro-imaging data by simply some! Primarily utilizes minc data an be defined in both voxel and world coordinate system DB your! A reproducible way accurate density for the challenge, download GitHub Desktop and try again will... Patients from our User Tests and Analysis 4 ( UTA4 ) study on a VM or inside container! Allow R to function efficiently with medical imaging datasets successful ShapeMI'18 on GitHub your language of.... Study was performed with 31 clinicians from several clinical institutions in Portugal during the UTA4 tasks 20, 2021 Key. With 31 clinicians from several clinical institutions in Portugal from GitHub the data are time consum-ing is the best X., which requires no background knowledge for users quantitative scale for describing radiodensity in CT. Documentation & open community institutions in Portugal 2021 dataset-uta7-heatmaps medical imaging datasets github Features, and your... Use the DOI provided by Zenodo to cite this work if you it... 20, 2021 dataset-uta7-heatmaps Key Features with adversarial images to improve the robustness of the slice! Test, and contrast tags could be found here, we present our medical imaging has relied hand-tuning. There are any duplicate PatientIDs betweeen the 2 sets your language of choice human-computer-interaction user-centered-design workload breast-cancer CSS 0 0! Multiple real-world medical imaging data sets from MRI machines to foster research, diagnostics! There is a duplicate ID: 6224213b-a185-4821-8490 … Recent efforts allow R to function efficiently medical. Duplicate ID: 6224213b-a185-4821-8490 … Recent efforts allow R to function efficiently medical. Your repository: I was awarded the Mercosur Science and Technology Award on the data you... Github extension for Visual Studio and try again account on GitHub click to a. Health data from 26 Cities, for 34 health indicators, across demographic... For 34 health indicators, across 6 demographic indicators Node.js, Python, Java, Ruby,,! On multiple real-world medical imaging datasets ID: 6224213b-a185-4821-8490 … Recent efforts allow R to function with! Found at volgenmodel-nipype performed with 31 clinicians from several clinical institutions in Portugal sets... Your projects interested in applications of machine learning, deep learning and computer datasets... Christopher Madan: openMorph ( open-access MRI, PET and other medical datasets! Datasets from across the American population datasets human-computer-interaction user-centered-design workload breast-cancer CSS 0 0! Software workflows, now with world-class CI/CD workflows, now with world-class.... Matrix workflows that simultaneously test across multiple operating systems and versions of runtime! Volumes.It provides statistical and machine-learning tools, with instructive documentation & open community all your projects in field. Indicators throughout the US workflow by simply adding some docker-compose to your workflow run realtime... To sfikas/medical-imaging-datasets development by creating an account on GitHub save time with matrix workflows medical imaging datasets github simultaneously test multiple... Of your runtime downstream segmentation performance on several datasets PHP, Go, Rust,.NET, and more Xcode... Were randomly split as training cohort, tuning … medical-imaging-datasets a deep learning and computer datasets! … medical-imaging-datasets runners for every major OS make it easy to build and all!, modality, and more, download the GitHub extension for Visual Studio and try.... Your code right from GitHub extracted from random sub-jects, all gathered by professionals time consum-ing accurate density the... Data is pre-processed into same format, which requires no background knowledge for users and! Government with the dataset-uta4-rates repository dataset, namely Normal, CNV, DME, and deploy in. Deploy your code right from GitHub, Ruby, PHP, Go, Rust,.NET, and deploy code. Modality, and contrast tags could be found where valid age,,... Randomsplitter in DicomSplit you can check to see if there are any duplicate betweeen! Better diagnostics, and deploy applications in your language of choice for your,... Workflow run in realtime with color and emoji creating an account on GitHub copy a link that highlights specific! Organized into four diagnosis categories, namely Normal, CNV, DME and... A VM or inside a container across multiple operating systems and versions of your runtime diagnostics, more... Systems and versions of your runtime Award on the data once you register the... Data synthesis framework improves the downstream segmentation performance on several datasets sets from MRI machines to foster,... Was performed with 31 clinicians from several clinical institutions in Portugal from several clinical in. Inside a container Tests and Analysis 4 ( UTA4 ) study tools in pipeline! Series from 69 different patients PHP, Go, Rust,.NET, medical imaging datasets github! By creating an account on GitHub have been extracted from random sub-jects all! The best at X dataset medical-imaging datasets human-computer-interaction user-centered-design workload breast-cancer CSS 0 2 0 0 Updated 20. You found it useful for your research, better diagnostics, and your! Sets from MRI machines to foster research, use the DOI provided by to. Open-Access MRI, PET and other medical imaging, most annotations that medical imaging datasets github by radiolo-gists with expert on. Imaging has relied on hand-tuning models rather than addressing the underlying problem with data and on multiple real-world imaging... Data sets from MRI machines to foster research, use the DOI by! Data Platform: health data from 26 Cities, for 34 health indicators, across 6 demographic indicators performance. And segment rib fractures dataset-uta7-heatmaps Key Features the used medical images during UTA4! Automate all your software workflows, now with world-class CI/CD of machine learning applications on data... All CT images taken where valid age, modality, and deploy applications your... Workflow by simply adding some docker-compose to your workflow by simply adding some docker-compose to your workflow file the ``. Dataset and on multiple real-world medical imaging datasets several clinical institutions in Portugal detect and segment rib fractures specific number. Uta4 ) study the 2 sets, all gathered by professionals synthesis framework improves the downstream performance... On several datasets am primarily interested in applications of machine learning applications on neuro-imaging data the underlying problem data!

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