Three-Dimensional Detection of Pulmonary Nodules in Chest CT Images


  •  Aliaa A. A. Youssif    
  •  Shereen A. Hussein    
  •  Ahmed S. Ibrahim    

Abstract

Small pulmonary nodules are radiologic findings that represent an important challenge in diagnosis systems. While these nodules are the major indicator for lung cancer and metastasis, their properties like size and location play an important role in classifying the benign one from the malignant. Estimating the growth rate of the nodule size states the degree of malignancy.
This paper presents a computer-aided diagnosis (CAD) system to detect small-size pulmonary nodules from the chest computed tomography (CT) images through two dimensional (2-D) and three-dimensional (3-D) methods. Also, a computed volumetric growth is a promising way to distinguish malignant from nonmalignant pulmonary nodules. It was applied to lung nodules (2 to 7 mm in diameter) and achieved sensitivity 94.6% with an average; it is expected to aid radiologists in the detection of small nodules on thin-section multi–detector row CT images.


This work is licensed under a Creative Commons Attribution 4.0 License.
  • ISSN(Print): 1913-8989
  • ISSN(Online): 1913-8997
  • Started: 2008
  • Frequency: semiannual

Journal Metrics

WJCI (2022): 0.636

Impact Factor 2022 (by WJCI):  0.419

h-index (January 2024): 43

i10-index (January 2024): 193

h5-index (January 2024): N/A

h5-median(January 2024): N/A

( The data was calculated based on Google Scholar Citations. Click Here to Learn More. )

Contact