Segmentation Of The Proximal Femur By The Analysis Of X-Ray Imaging Using Statistical Models Of Shape And Appearance

ARTIFICIAL INTELLIGENCE AND SOFT COMPUTING (ICAISC 2018), PT II(2018)

引用 2|浏览3
暂无评分
摘要
Using image processing to assist in the diagnostic of diseases is a growing challenge. Segmentation is one of the relevant stages in image processing. We present a strategy of complete segmentation of the proximal femur (right and left) in anterior-posterior pelvic radiographs using statistical models of shape and appearance for assistance in the diagnostics of diseases associated with femurs. Quantitative results are provided using the DICE coefficient and the processing time, on a set of clinical data that indicate the validity of our proposal.
更多
查看译文
关键词
Segmentation, AP X-ray, Statistical shape models (SSM), Statistical appearance models (SAM), Gold standard, DICE coefficient
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要