Selected article for: "classification segmentation and feature representation"
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_15
    Snippet: We have developed a new MTL architecture based on 3 tasks: 1) COVID vs non-COVID classification, 2) COVID lesion segmentation, 3) Image reconstruction. The two first tasks are essential ones, while the third task is added to enhance the feature representation extracted. In this work we choose to use a hard parameter sharing to share parameters between the different tasks. We create a common encoder for the three tasks which takes a CT scan as inp.....
    Document: We have developed a new MTL architecture based on 3 tasks: 1) COVID vs non-COVID classification, 2) COVID lesion segmentation, 3) Image reconstruction. The two first tasks are essential ones, while the third task is added to enhance the feature representation extracted. In this work we choose to use a hard parameter sharing to share parameters between the different tasks. We create a common encoder for the three tasks which takes a CT scan as input, and its output is then used to the reconstruction of the image via a first decoder, and to the segmentation via a second decoder, and to the classification of COVID and non-COVID image via a multi-layer perceptron (see Fig 4) .

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