{"payload":{"pageCount":1,"repositories":[{"type":"Public","name":"ENIGMA","owner":"DEPREDICT","isFork":false,"description":"","allTopics":[],"primaryLanguage":{"name":"Jupyter Notebook","color":"#DA5B0B"},"pullRequestCount":0,"issueCount":0,"starsCount":1,"forksCount":0,"license":"Apache License 2.0","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-09-05T08:16:12.749Z"}},{"type":"Public","name":"sphere2dice","owner":"DEPREDICT","isFork":false,"description":"Sphere2dice converts Cortical Brain Morphometry data from FreeSurfer or Gifty type into a stack of 2D images and saves is as numpy array. This stack of images is easier to use as input to conventional CNNs, while avoiding projection issues other methods suffer from. ","allTopics":["machine-learning","cnn","neuroimaging","cortical-surfaces","freesurfer","cortical-thickness"],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":0,"starsCount":1,"forksCount":0,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2023-04-17T00:02:50.867Z"}},{"type":"Public","name":"SLEEEP","owner":"DEPREDICT","isFork":false,"description":"code, data and documentation behind the publication: Robustness Of Radiomics To Variations In Segmentation Methods In Multimodal Brain MRI","allTopics":["deep-learning","medical-imaging","segmentation","convolutional-neural-networks"],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":0,"starsCount":0,"forksCount":1,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2022-10-22T10:46:39.447Z"}}],"repositoryCount":3,"userInfo":null,"searchable":true,"definitions":[],"typeFilters":[{"id":"all","text":"All"},{"id":"public","text":"Public"},{"id":"source","text":"Sources"},{"id":"fork","text":"Forks"},{"id":"archived","text":"Archived"},{"id":"template","text":"Templates"}],"compactMode":false},"title":"DEPREDICT repositories"}