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Published in: Journal of Digital Imaging 1/2011

01-02-2011

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

Authors: Xiuhua Guo, Xiangye Liu, Huan Wang, Zhigang Liang, Wei Wu, Qian He, Kuncheng Li, Wei Wang

Published in: Journal of Imaging Informatics in Medicine | Issue 1/2011

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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.
Literature
1.
go back to reference Li F, Sone S, Abe H, Macmahon H, Doi K: Malignant versus benign nodules at CT screening for lung cancer: comparison of thin-section CT findings. Radiology 233(3):793–798, 2004CrossRefPubMed Li F, Sone S, Abe H, Macmahon H, Doi K: Malignant versus benign nodules at CT screening for lung cancer: comparison of thin-section CT findings. Radiology 233(3):793–798, 2004CrossRefPubMed
2.
go back to reference Öktem H, Egiazarian K, Niittylahti J, Lemmetti J, Latvala J: A wavelet based algorithm for simultaneous x-ray image de-noising and enhancement. In Proc. 2nd International Conference on Information, Communications & Signal Processing (ICICS ’99), Singapore, December 1999 Öktem H, Egiazarian K, Niittylahti J, Lemmetti J, Latvala J: A wavelet based algorithm for simultaneous x-ray image de-noising and enhancement. In Proc. 2nd International Conference on Information, Communications & Signal Processing (ICICS ’99), Singapore, December 1999
3.
go back to reference Öktem H, Egiazarian K, Niittylahti J, Lemmetti J: An approach to adaptive enhancement of diagnostic x-ray images. EURASIP J Appl Signal Process 5:430–436, 2003 Öktem H, Egiazarian K, Niittylahti J, Lemmetti J: An approach to adaptive enhancement of diagnostic x-ray images. EURASIP J Appl Signal Process 5:430–436, 2003
4.
go back to reference Yang GZ, Hansell DM: Hansell: CT image enhancement with wavelet analysis for the detection of small airways disease. IEEE Trans Med Imag 16(6):953–961, 1997CrossRef Yang GZ, Hansell DM: Hansell: CT image enhancement with wavelet analysis for the detection of small airways disease. IEEE Trans Med Imag 16(6):953–961, 1997CrossRef
6.
go back to reference Jin ATB, Ling DNC, Song OT: An efficient fingerprint verification system using integrated wavelet and Fourier-Mellin invariant transform. Image Vis Comput 22:503–513, 2004CrossRef Jin ATB, Ling DNC, Song OT: An efficient fingerprint verification system using integrated wavelet and Fourier-Mellin invariant transform. Image Vis Comput 22:503–513, 2004CrossRef
7.
go back to reference Swensen SJ, Jett JR, Sloan JA, Midthun DE, Hartman TE, Sykes AM, et al: Screening for lung cancer with low-dose spiral computed tomography. Am J Respir Crit Care Med 165(4):508–513, 2002PubMed Swensen SJ, Jett JR, Sloan JA, Midthun DE, Hartman TE, Sykes AM, et al: Screening for lung cancer with low-dose spiral computed tomography. Am J Respir Crit Care Med 165(4):508–513, 2002PubMed
8.
go back to reference Swensen SJ, Jett JR, Hartman TE, Midthun DE, Sloan JA, Sykes AM, Aughenbaugh GL, Clemens MA: Lung cancer screening with CT: Mayo Clinic experience. Radiology 226(3):756–761, 2003CrossRefPubMed Swensen SJ, Jett JR, Hartman TE, Midthun DE, Sloan JA, Sykes AM, Aughenbaugh GL, Clemens MA: Lung cancer screening with CT: Mayo Clinic experience. Radiology 226(3):756–761, 2003CrossRefPubMed
9.
go back to reference Sone S, Li F, Yang ZG, Takashima S, Maruyama Y, Hasegawa M, Wang JC, Kawakami S, Honda T: Characteristics of small lung cancers invisible on conventional chest radiography and detected by population based screening using spiral CT. Br J Radiol 73(866):137–145, 2000PubMed Sone S, Li F, Yang ZG, Takashima S, Maruyama Y, Hasegawa M, Wang JC, Kawakami S, Honda T: Characteristics of small lung cancers invisible on conventional chest radiography and detected by population based screening using spiral CT. Br J Radiol 73(866):137–145, 2000PubMed
10.
go back to reference Sluimer I, Schilham A, Prokop M, van Ginneken B: Computer analysis of computed tomography scans of the lung: a survey. IEEE Trans Med Imag 25(4):385–405, 2006CrossRef Sluimer I, Schilham A, Prokop M, van Ginneken B: Computer analysis of computed tomography scans of the lung: a survey. IEEE Trans Med Imag 25(4):385–405, 2006CrossRef
Metadata
Title
Enhanced CT Images by the Wavelet Transform Improving Diagnostic Accuracy of Chest Nodules
Authors
Xiuhua Guo
Xiangye Liu
Huan Wang
Zhigang Liang
Wei Wu
Qian He
Kuncheng Li
Wei Wang
Publication date
01-02-2011
Publisher
Springer-Verlag
Published in
Journal of Imaging Informatics in Medicine / Issue 1/2011
Print ISSN: 2948-2925
Electronic ISSN: 2948-2933
DOI
https://doi.org/10.1007/s10278-009-9248-y

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