Suppr超能文献

使用主动形状模型和GVF蛇模型从临床CT图像中分割腰椎。

Segmentation of lumbar vertebrae from clinical CT using active shape models and GVF-snake.

作者信息

Al-Helo Samah, Alomari Raja' S, Chaudhary Vipin, Al-Zoubi M B

机构信息

Dept of Computer Information Systems, University of Jordan, Amman 11942, Jordan.

出版信息

Annu Int Conf IEEE Eng Med Biol Soc. 2011;2011:8033-6. doi: 10.1109/IEMBS.2011.6091981.

Abstract

Lumbar area of the vertebral column bears the most load of the human body and thus it is responsible for the major portion of lower back pain from which 80% to 90% of people suffer from during their lifetime. Vertebra related diseases are mainly fracture and are usually diagnosed from X-ray radiographs or CT scans depending on the severity of the problem. In this paper, we propose a fully automated lumbar vertebra segmentation that accurately and robustly produces a smooth contour around each of the vertebrae. This segmentation is very useful in any subsequent CAD system for diagnosis and quantification of vertebrae fractures. It also serves the radiologist during the clinical routine. Our method shows an excellent level of vertebra boundary smootheness that was visually approved by our collaborating radiologist for each vertebra and each case from our fifty cases dataset that includes both normal and abnormal cases.

摘要

脊柱的腰部承受着人体最大的负荷,因此它是导致下背部疼痛的主要原因,80%至90%的人在一生中都会遭受这种疼痛。与椎骨相关的疾病主要是骨折,通常根据问题的严重程度通过X光片或CT扫描进行诊断。在本文中,我们提出了一种全自动腰椎分割方法,该方法能够准确、稳健地在每个椎骨周围生成平滑的轮廓。这种分割在任何后续用于诊断和量化椎骨骨折的CAD系统中都非常有用。它在临床常规工作中也能为放射科医生提供帮助。我们的方法显示出了出色的椎骨边界平滑度,我们合作的放射科医生对我们五十个病例的数据集(包括正常和异常病例)中的每个椎骨和每个病例进行了视觉认可。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验