Journal of Digital Imaging

, Volume 24, Issue 1, pp 44–49 | Cite as

Enhanced CT Images by the Wavelet Transform Improving Diagnostic Accuracy of Chest Nodules

Article

Abstract

The objective of this study was to compare the diagnostic accuracy in the interpretation of chest nodules using original CT images versus enhanced CT images based on the wavelet transform. The CT images of 118 patients with cancers and 60 with benign nodules were used in this study. All images were enhanced through an algorithm based on the wavelet transform. Two experienced radiologists interpreted all the images in two reading sessions. The reading sessions were separated by a minimum of 1 month in order to minimize the effect of observer’s recall. The Mann–Whitney U nonparametric test was used to analyze the interpretation results between original and enhanced images. The Kruskal–Wallis H nonparametric test of K independent samples was used to investigate the related factors which could affect the diagnostic accuracy of observers. The area under the ROC curves for the original and enhanced images was 0.681 and 0.736, respectively. There is significant difference in diagnosing the malignant nodules between the original and enhanced images (z = 7.122, P < 0.001), whereas there is no significant difference in diagnosing the benign nodules (z = 0.894, P = 0.371). The results showed that there is significant difference between original and enhancement images when the size of nodules was larger than 2 cm (Z = −2.509, P = 0.012, indicating the size of the nodules is a critical evaluating factor of the diagnostic accuracy of observers). This study indicated that the image enhancement based on wavelet transform could improve the diagnostic accuracy of radiologists for the malignant chest nodules.

Key words

Wavelet transform chest nodules enhanced CT 

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Copyright information

© Society for Imaging Informatics in Medicine 2009

Authors and Affiliations

  1. 1.Department of Epidemiology and Health Statistics, School of Public Health and Family MedicineCapital Medical UniversityBeijingChina
  2. 2.Department of Radiology, Xuanwu HospitalCapital Medical UniversityBeijingChina
  3. 3.Department of Radiology, Beijing Friendship HospitalCapital Medical UniversityBeijingChina

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