Lung nodule segmentation in chest computed tomography using a novel background estimation method

Quantitative Imaging in Medicine and Surgery

Crystal Fong²  Jane Castelli²  David Koff²  Jacob Scharcanski³  Pablo G. Cavalcanti⁴  Jane Meng¹  Shahram Shirani⁵ 

[1] Michael G. DeGroote School of Medicine, McMaster University, Hamilton, ON, CanadaDepartment of Radiology, Faculty of Health Sciences, McMaster University, Hamilton, ON, Canada;Institute of Informatics, Federal University of Rio Grande do Sul, Porto Alegre, RS, Brazil;Department of Informatics, Federal University of Technology–Paraná, Via do Conhecimento Km 1, Pato Branco, PR, Brazil;Department of Electrical and Computer Engineering, McMaster University, Hamilton, ON, Canada;

关键词: Lung nodules;    segmentation;    background estimation;    chest CT;   

DOI  :  10.3978/j.issn.2223-4292.2016.02.06

学科分类：外科医学

来源: AME Publications

【 摘 要 】

Background: Lung cancer results in the highest number of cancer deaths worldwide. The segmentation of lung nodules is an important task in computer systems to help physicians differentiate malignant lesions from benign lesions. However, it has already been observed that this may be a difficult task, especially when nodules are connected to an anatomical structure.

Methods: This paper proposes a method to estimate the background of the nodule area and how this estimation is used to facilitate the segmentation task.

Results: Our experiments indicate more than 99% of accuracy with less than 1% of false positive rate (FPR).

Conclusions: The proposed methods achieved better results than a state-of-the-art approach, indicating potential to be used in medical image processing systems.

【 授权许可】

Unknown