DocumentCode :
2396495
Title :
A Texture-based Morphologic Enhancement Filter in Two-dimensional Thoracic CT scans
Author :
Yu, Yang ; Zhao, Hong
Author_Institution :
Dept. of Comput. Sci., Northeastern Univ., Shenyang
fYear :
0
fDate :
0-0 0
Firstpage :
850
Lastpage :
855
Abstract :
This paper presents a novel enhancement filter as a preprocessing step in the early detection of lung cancer. The identification and enhancement of the nodular structures is the initial stage in computer-aided diagnosis (CAD) for improving the sensitivity of nodule detection and reducing the number of false positives. Based on nodular texture feature and mathematical morphology, our proposed enhancement filter is simpler and automatic to extract and enhance the contrast of the region of interests (ROI) in thoracic computer tomography (CT) images. The proposed algorithm consists of the segmentation methods using gray-scale threshold, mathematical morphologic analysis and texture-based segmentation, and the enhancement method using contrast limiting adaptive histogram equalization (CLAHE). In our preprocessing stage, the automated segmentation and reconstruction of the pulmonary parenchyma has been performed. Then the ROI extraction based on nodular texture has been processed. Finally, the contrast of the ROI is enhanced by CLAHE. We applied our enhancement filter to two-dimensional (2D) CT images from LIDC using DICOM standards to show its effectiveness in the enhancement of the ROI. We believe that the enhancement filter developed in this study would be useful in the automated detection of nodules in 2D medical images
Keywords :
cancer; computerised tomography; feature extraction; filters; image enhancement; image reconstruction; image segmentation; image texture; mathematical morphology; medical image processing; 2D medical images; DICOM standards; LIDC; automated texture-based segmentation; computer-aided diagnosis; contrast limiting adaptive histogram equalization; enhancement method; false positives; gray-scale threshold; lung cancer detection; mathematical morphologic analysis; nodular texture feature; nodule detection; pulmonary parenchyma reconstruction; region-of-interest extraction; texture-based morphologic enhancement filter; thoracic computer tomography images; two-dimensional thoracic CT scans; Algorithm design and analysis; Cancer detection; Computed tomography; Computer aided diagnosis; Filters; Gray-scale; Image segmentation; Image texture analysis; Lungs; Morphology;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Networking, Sensing and Control, 2006. ICNSC '06. Proceedings of the 2006 IEEE International Conference on
Conference_Location :
Ft. Lauderdale, FL
Print_ISBN :
1-4244-0065-1
Type :
conf
DOI :
10.1109/ICNSC.2006.1673258
Filename :
1673258
Link To Document :
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