Literature DB >> 18003267

An efficient method of automatic pulmonary parenchyma segmentation in CT images.

Zhaoxue Chen1, Xiwen Sun, Shengdong Nie.   

Abstract

Based on special distributing characteristics of pixel intensity in lung CT images, an efficient lung segmentation method is introduced. Associating approach of image threshold with fast region flood filling technique, this method can extract pulmonary parenchyma from CT images simply. After a preprocessing step for noise removal, it segments the lung CT image slice utilizing a threshold method at first, and then applies a fast and simple method to finish flood filling of the non-lung area. In the following steps, the lung area can be extracted automatically after an erosion operation and an area-filtering step. The presented experiment results have proved its validity.

Entities:  

Mesh:

Year:  2007        PMID: 18003267     DOI: 10.1109/IEMBS.2007.4353601

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  2 in total

1.  A novel supervised approach for segmentation of lung parenchyma from chest CT for computer-aided diagnosis.

Authors:  Shiloah Elizabeth Darmanayagam; Khanna Nehemiah Harichandran; Sunil Retmin Raj Cyril; Kannan Arputharaj
Journal:  J Digit Imaging       Date:  2013-06       Impact factor: 4.056

Review 2.  Machine learning techniques for CT imaging diagnosis of novel coronavirus pneumonia: a review.

Authors:  Jingjing Chen; Yixiao Li; Lingling Guo; Xiaokang Zhou; Yihan Zhu; Qingfeng He; Haijun Han; Qilong Feng
Journal:  Neural Comput Appl       Date:  2022-09-19       Impact factor: 5.102

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.