Automated Kidney Detection and Segmentation in 3D Ultrasound

被引：12

作者：

Noll, Matthias ^{[1
]}

Li, Xin ^{[1
]}

Wesarg, Stefan ^{[1
]}

机构：

[1] Fraunhofer IGD, Cognit Comp & Med Imaging, Darmstadt, Germany

来源：

CLINICAL IMAGE-BASED PROCEDURES: TRANSLATIONAL RESEARCH IN MEDICAL IMAGING | 2014年 / 8361卷

关键词：

Ultrasound; Image analysis; Kidney; Shape prior; Detection; Segmentation; ENHANCEMENT;

D O I：

10.1007/978-3-319-05666-1_11

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Ultrasound provides the physical capabilities for a fast and save disease diagnosis in various medical scenarios including renal exams and patient trauma assessment. However, the experience of the ultrasound operator is the key element in performing ultrasound diagnosis. Thus, we like to introduce our automatic kidney detection and segmentation algorithm for 3D ultrasound. The approach utilizes basic kidney shape information to detect the kidney position. Following, the Level Set algorithm is applied to segment the detection result. In combination this method may help physicians and inexperienced trainees to achieve kidney detection and segmentation for diagnostic purposes.

引用

页码：83 / 90

页数：8

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