Automated Segmentation for Patella from Lateral Knee X-ray Images

Chia Nan University of Pharmacy & Science Institutional Repository > 環境永續暨休閒學院 > 應用空間資訊系(所) > 會議論文 > Item 310902800/24771

請使用永久網址來引用或連結此文件: https://ir.cnu.edu.tw/handle/310902800/24771

標題:	Automated Segmentation for Patella from Lateral Knee X-ray Images
作者:	H.C. Chen C.H. Wu C.J. Lin Y.H. Liu Y.N. Sun
貢獻者:	應用空間資訊系
日期:	2009-09-02
上傳時間:	2011-11-14 14:31:31 (UTC+8)
摘要:	X-ray image segmentation is an important issue in medical image analysis. Due to inconsistent X-ray absorption, the intensities are usually unevenly distributed and noisy in the processed organ, thus the object segmentation becomes difficult. In this paper we propose a new segmentation method for patella from the lateral knee X-ray images based on the active shape model (ASM). At first, a patella shape model is constructed by principal component analysis (PCA) of corresponding landmarks obtained from a set of training shape. As the knee X-ray image usually contains many anatomical structures, we design a strategy based on edge tracing to place the initial shape model as close to the patella boundary as possible. Then, the shape model is deformed and fitted to the patella boundary by using a dual-optimization approach that includes a genetic algorithm (GA) to get the global geometric transform and ASM to deform the shape model iteratively. Consequently, the proposed method can cope with different knee X-ray images and can segment the patella in an automatic procedure. In the experiment, 20 images were tested and promising results are obtained by the proposed method. This method is found useful for the clinical evaluation and biomechanical study of knee.
關聯:	31th Annual International Conference of the IEEE Engineering in Medicine and Biology Society，起迄日：2009/9/2~2009/9/6，地點：Minnesota
顯示於類別:	[應用空間資訊系(所)] 會議論文

文件中的檔案:

沒有與此文件相關的檔案.

在CNU IR中所有的資料項目都受到原著作權保護.

TAIR相關文章

資料載入中.....