A Comparative Texture Analysis Based on NECT and CECT Images to Differentiate Lung Adenocarcinoma from Squamous Cell Carcinoma

  • Han Liu
  • Bin Jing
  • Wenjuan Han
  • Zhuqing Long
  • Xiao Mo
  • Haiyun LiEmail author
Image & Signal Processing
Part of the following topical collections:
  1. Image & Signal Processing


The purpose of the study was to compare the texture based discriminative performances between non-contrast enhanced computed tomography (NECT) and contrast-enhanced computed tomography (CECT) images in differentiating lung adenocarcinoma (ADC) from squamous cell carcinoma (SCC) patients. Eighty-seven lung cancer subjects were enrolled in the study, including pathologically proved 47 ADC patients and 40 SCC patients, and 261 texture features were extracted from the manually delineated region of interests on CECT and NECT images respectively. Fisher score was then used to select the effective discriminative texture features between groups, and the selected texture features were adopted to differentiate ADC from SCC using Support Vector Machine and Leave-one-out cross-validation. Both NECT and CECT images could achieve the same best classification accuracy of 95.4%, and most of the informative features were from the gray-level co-occurrence matrix. In addition, CECT images were found with enhanced texture features compared with NECT images, and combining texture features of CECT and NECT images together could further improve the prediction accuracy. Besides the texture feature, the tumor location information also contributed to the differential diagnosis between ADC and SCC.


Texture analysis Lung adenocarcinoma Squamous cell carcinoma Non-contrast enhanced computed tomography Contrast enhanced computed tomography 



This work was supported by National Natural Science Foundation of China (grant numbers 81220108007), Beijing Natural Science Foundation (No. 4122018). Bin Jing was supported by Beijing Natural Science Foundation (No. 7174282).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the national research committee.

Informed consent

For this type of study formal consent is not required.


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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • Han Liu
    • 1
  • Bin Jing
    • 1
  • Wenjuan Han
    • 2
  • Zhuqing Long
    • 1
  • Xiao Mo
    • 1
  • Haiyun Li
    • 1
    Email author
  1. 1.School of Biomedical EngineeringCapital Medical UniversityBeijingChina
  2. 2.Department of Radiologythe General Hospital of Chinese People’s Armed Police ForcesBeijingChina

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