Detection and retrieval of cysts in joint ultrasound B-mode and elasticity breast images

Jingdan Zhang, S. Zhou, S. Brunke, C. Lowery, D. Comaniciu
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引用次数: 8

Abstract

Distinguishing cysts from other tumors is a routine clinical practice for diagnosing breast cancer. It has shown that more accurate diagnosis can be achieved by combining elasticity images with traditional B-mode ultrasound images [1]. In this paper, we propose a fully automatic system to detect cysts jointly in both B-mode and elasticity images. It is based on database-guided techniques that learn the knowledge of cyst appearance automatically from B-mode and elasticity images in a database. Further, for a detected cyst in a query image, the cysts with similar image appearance in the database are retrieved to improve diagnostic accuracy and confidence. In the experiment, we show that our system achieves high sensitivity and specificity in cyst diagnosis.
关节超声b型和弹性乳房图像中囊肿的检测和恢复
将囊肿与其他肿瘤区分开来是诊断乳腺癌的常规临床实践。研究表明,将弹性图像与传统b超图像相结合可以获得更准确的诊断[1]。在本文中,我们提出了一个全自动的系统来检测囊肿在b模式和弹性图像。它基于数据库引导技术,从数据库中的b模式和弹性图像中自动学习囊肿外观的知识。此外,对于查询图像中检测到的囊肿,检索数据库中具有相似图像外观的囊肿,以提高诊断准确性和置信度。实验结果表明,该系统对囊肿的诊断具有较高的敏感性和特异性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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