A multi-scale matched filter based on Hotelling classifier is presented to improve the accuracy of nodule detection in chest X-ray radiography. The positive and negative radiography samples are used to train multi-dimension matched filters by Hotelling model. The visual detection difference is calculated using the filter outputs of radiography
and the optimal dimension filter is searched subject to the maximum detection difference. Then the nodule size and detection capability are calculated based on the optimal filter. Experimental results show that there is good accordance of the detection performances between the presented method and subjective observers. The method improves the detection accuracy and reduces the false-positive regions in the processed images. Errors of the calculated relative nodule sizes mainly distribute between -0.21 and 0.18 and the proportion of the images in this range is 86%.
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SCHNEIDER C, AMJADI A, RICHTER A, et al. Automated lung nodule detection and segmentation [EB/OL]. [2010-08-16]. http:∥spie.org/x648.html?product_id=811985.
TSENG L Y, HUANG L C. An adaptive thresholding method for automatic lung segmentation in CT images [C]∥Proceedings of the 9th IEEE AFRICON. Piscataway, NJ, USA: IEEE, 2009: 1-5.
CAO Lei, ZHAN Jie, YU Xiaoe, et al. Fast lung segmentation algorithm for thoracic CT based on automated thresholding[J]. Journal of Computer Engineering and Applications, 2008, 12(44): 178-181.
SUN Hailin, ZHANG Xiaopeng, TANG Lei, et al. Three-dimensional volumetric measurement of pulmonary nodules by 64-MSCT with segmentation threshold algorithm: experimental study [J]. Chin J Med Imaging Technol, 2008, 24(8): 1157-1161.
DEHMESHKI J, AMIN H. Segmentation of pulmonary nodules in thoracic CT scans: a region growing approach [J]. IEEE Transactions on Medical Imaging, 2008, 27(4): 467-480.
YANG Runling, GAO Xinbo. A fast automatic image segmentation algorithm based on weighting fuzzy c-means clustering [J]. Journal of Image and Graphics, 2007, 12(12): 2105-2112.
SHIRAISHI J, LI Qiang, DOI K. Development of a computerized scheme for detection of very subtle lung nodules located in opaque areas on chest radiographs [EB/OL]. [2010-08-16]. http:∥spie.org/x648.html?product_id=652456.
束洲. 肺结节计算机辅助诊断算法研究[D]. 浙江:浙江大学理学院,2007.
KUPINSKI M A, CLARKSON E, HESTERMAN J Y. Bias in Hotelling observer performance computed from finite data [EB/OL]. [2010-08-16]. http:∥spie.org/x648.html? product_id=707800.
YAO Jie, BARRETT H H. Predicting human performance by a channelized Hotelling observer model [C]∥Proceedings of SPIE Conference in Mathematical Methods in Medical Imaging. San Diego, CA, USA: SPIE, 1992: 161-168.
PARK S, BARRETT H H, CLARKSON E, et al. Channelized-ideal observer using Laguerre-Gauss channels in detection tasks involving non-Gaussian distributed lumpy backgrounds and a Gaussian signal [J]. J Opt Soc Am: A, 2007, 24(12): 136-150.