February 16, 2023 Software Open Access

Lizzi Francesca; Postuma Ian; Cabini Raffaella; Brero Francesca; Fantacci M. Evelina; Lascialfari Alessandro; Oliva Piernicola; Retico Alessandra

Citation Style Language JSON Export

{
  "DOI": "10.15161/oar.it/76937", 
  "abstract": "<p>LungQuant is a software for the quantification of lesions in CT scans of COVID-19 patients.</p>\n\n<p>Its functioning is based on a cascade of three Convolutional Neural Networks (CNN):</p>\n\n<p>1) the first one is used to produce a bounding box enclosing the lungs;</p>\n\n<p>2) the second CNN is used to segment the lungs;</p>\n\n<p>3) the third CNN is devoted to lesion segmentation.</p>\n\n<p>The system takes in input&nbsp; Computed Tomography (CT) scans in nifti format.</p>\n\n<p>The system returns in output: the lungs and lesion masks and other information that can be useful to describe the infection.</p>", 
  "author": [
    {
      "family": "Lizzi Francesca"
    }, 
    {
      "family": "Postuma Ian"
    }, 
    {
      "family": "Cabini Raffaella"
    }, 
    {
      "family": "Brero Francesca"
    }, 
    {
      "family": "Fantacci M. Evelina"
    }, 
    {
      "family": "Lascialfari Alessandro"
    }, 
    {
      "family": "Oliva Piernicola"
    }, 
    {
      "family": "Retico Alessandra"
    }
  ], 
  "id": "76937", 
  "issued": {
    "date-parts": [
      [
        2023, 
        2, 
        16
      ]
    ]
  }, 
  "language": "eng", 
  "title": "LungQuant", 
  "type": "article", 
  "version": "2.5"
}