Noll, Matthias ; Li, Xin ; Wesarg, Stefan (2014)
Automated Kidney Detection and Segmentation in 3D Ultrasound.
Clinical Image-Based Procedures. Translational Research in Medical Imaging.
doi: 10.1007/978-3-319-05666-1_11
Conference or Workshop Item, Bibliographie
Abstract
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.
| Item Type: | Conference or Workshop Item |
|---|---|
| Erschienen: | 2014 |
| Creators: | Noll, Matthias ; Li, Xin ; Wesarg, Stefan |
| Type of entry: | Bibliographie |
| Title: | Automated Kidney Detection and Segmentation in 3D Ultrasound |
| Language: | English |
| Date: | 2014 |
| Publisher: | Springer, Berlin, Heidelberg, New York |
| Series: | Lecture Notes in Computer Science (LNCS); 8361 |
| Event Title: | Clinical Image-Based Procedures. Translational Research in Medical Imaging |
| DOI: | 10.1007/978-3-319-05666-1_11 |
| Abstract: | 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. |
| Uncontrolled Keywords: | Business Field: Visual decision support, Research Area: Computer vision (CV), Ultrasound, Image analysis, Shape priors, Detection, Segmentation |
| Divisions: | 20 Department of Computer Science 20 Department of Computer Science > Interactive Graphics Systems |
| Date Deposited: | 12 Nov 2018 11:16 |
| Last Modified: | 12 Nov 2018 11:16 |
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