Статья

Segmentation of Lungs, Lesions, and Lesion Types on Chest CT Scans of Patients with Covid-19

D. Lashchenova, A. Gromov, A. Konushin, A. Mesheryakova,
2020

The covid-19 pandemic has quickly spread all over the world, overwhelming public healthcare systems in many countries. In this situation demand for automatic assistance systems, to facilitate and accelerate a doctor’s job has rapidly increased. Antibody tests were introduced for diagnosing covid-19, but physicians still need tools for quantification of disease severity, since treatment choice strongly depends on it. To estimate the severity of the disease physicians use computer tomography scans. It provides physicians with information about lung lesions and their types and they use this information to determine proper treatment. In this paper we made an attempt to build a system that uses patients’ computer tomography scans for lung and lesion segmentation and for segmentation of specific types of lesions (i.e. pulmonary consolidation and “crazypaving”). Models for lung, lesions, consolidation, and “crazy-paving” segmentation performed with 0.96, 0.65, 0.48, 0.45 Dice coefficients respectively. Also it was shown that removing images with inaccurate ground-truth from the training subset can improve the quality of models trained on it.

Цитирование

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Версии

  • 1. Version of Record от 2020-12-17

Метаданные

Об авторах
  • D. Lashchenova
    Lomonosov Moscow State University
  • A. Gromov
    Lomonosov Moscow State University
  • A. Konushin
    Lomonosov Moscow State University
  • A. Mesheryakova
    Third Opinion Platform LLC
Страницы
  • short20-1-short20-9
Тип документа
  • journal article
Тип лицензии Creative Commons
  • CC BY
Правовой статус документа
  • Свободная лицензия
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