文章基本信息

标题：A NOVEL APPROACH TO DETECT FISSURES IN LUNG CT IMAGES USING MARKER-BASED WATERSHED TRANSFORMATION
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作者：Devaki, K. ; Bhaskaran, V. Murali
期刊名称：Journal of Computer Science
印刷版ISSN：1549-3636
出版年度：2014
卷号：10
期号：6
页码：896-905
DOI：10.3844/jcssp.2014.896.905
出版社：Science Publications
摘要：Detection and segmentation of fissures is useful in the clinical interpretation of CT lung images to diagnose the presence of pathologies in the human lungs. A new automated method based on marker-based watershed transformation has been proposed to segment the fissures considering its unique structure as a long connected component. Marker based watershed transformation is applied and morphological operations are employed to specify the internal and external markers. The smaller regions in the resulting image are removed by a novel procedure called Small Segment Removal Algorithm (SSRA) to segment the fissures alone. The performance of the method is validated by experimenting with 6 CT image sets. An expert radiologist observation is used as reference to assess the performance. A promising accuracy of 96.61% is shown with the rms error in the range of 0.877±0.224 mm for the left oblique fissure and 0.803±0.262 mm for the right oblique fissure.
关键词：Lung CT Image; Segmentation; Detection; Fissures; Marker Based Watershed