Selected article for: "infection segmentation and segmentation task"
Author: Amine Amyar; Romain Modzelewski; Su Ruan
Title: Multi-task Deep Learning Based CT Imaging Analysis For COVID-19: Classification and Segmentation
  • Document date: 2020_4_21
    • ID: hiac6ur7_39
    Snippet: For the validating methodology, we split the data for training, validation and test as shown in Table 1 . Among the 349 COVID cases in the training, the ground truth for the infection label (segmentation task) was available for 50 CT scans. Twenty others were in the validation and thirty in the test set. For non-COVID cases, different kinds of pathology such as . CC-BY-NC-ND 4.0 International license It is made available under a author/funder, wh.....
    Document: For the validating methodology, we split the data for training, validation and test as shown in Table 1 . Among the 349 COVID cases in the training, the ground truth for the infection label (segmentation task) was available for 50 CT scans. Twenty others were in the validation and thirty in the test set. For non-COVID cases, different kinds of pathology such as . CC-BY-NC-ND 4.0 International license It is made available under a author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

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