1 Ocak 2018 Dergi makalesi Açık Erişim

Doganay, Emine; Kara, Sada; Ozcelik, Hatice Kutbay; Kart, Levent

Citation Style Language JSON

{
  "DOI": "10.1080/21681163.2017.1332531", 
  "abstract": "The lung is an essential organ and is dark in Computed Tomography (CT) images because of air. Lung segmentation and correct lung region separation is a prerequisite for the development of computer-aided diagnostic algorithms and disease treatment planning. However, this remains a nontrivial problem because of lung anatomical structures. Here, we addressed this problem and proposed a reliable and robust solution that is based on a histogram-based fuzzy C-means (FCM) algorithm and morphological mathematical algorithms. There were 1632 high resolution CT slices with 1 mm thickness used from asthma patients with low dose; right and left lungs were classified using the proposed algorithm. We extracted right lung regions with 96.05% accuracy and left lung regions at 96.32%. The computation time is 1.3 s per slice.", 
  "author": [
    {
      "family": "Doganay", 
      "given": " Emine"
    }, 
    {
      "family": "Kara", 
      "given": " Sada"
    }, 
    {
      "family": "Ozcelik", 
      "given": " Hatice Kutbay"
    }, 
    {
      "family": "Kart", 
      "given": " Levent"
    }
  ], 
  "container_title": "COMPUTER METHODS IN BIOMECHANICS AND BIOMEDICAL ENGINEERING-IMAGING AND VISUALIZATION", 
  "id": "33693", 
  "issue": "6", 
  "issued": {
    "date-parts": [
      [
        2018, 
        1, 
        1
      ]
    ]
  }, 
  "page": "638-648", 
  "title": "A hybrid lung segmentation algorithm based on histogram-based fuzzy C-means clustering", 
  "type": "article-journal", 
  "volume": "6"
}