Jung, Florian ; Kirschner, Matthias ; Wesarg, Stefan (2013)
A Generic Approach to Organ Detection Using 3D Haar-Like Features.
Bildverarbeitung für die Medizin 2013.
doi: 10.1007/978-3-642-36480-8_56
Conference or Workshop Item, Bibliographie
Abstract
Automatic segmentation of medical images requires accurate detection of the desired organ as a first step. In contrast to application specific approaches, learning-based object detection algorithms are easily adaptable to new applications. We present a learning-based object detection approach based on the Viola-Jones algorithm. We propose several extensions to the original approach, including a new 3D feature type and a multi-organ detection scheme. The algorithm is used to detect six different organs in CT scans as well as the prostate in MRI data. Our evaluation shows that the algorithm provides fast and reliable detection results in all cases.
| Item Type: | Conference or Workshop Item |
|---|---|
| Erschienen: | 2013 |
| Creators: | Jung, Florian ; Kirschner, Matthias ; Wesarg, Stefan |
| Type of entry: | Bibliographie |
| Title: | A Generic Approach to Organ Detection Using 3D Haar-Like Features |
| Language: | English |
| Date: | 2013 |
| Publisher: | Springer, Berlin; Heidelberg; New York |
| Series: | Informatik aktuell |
| Event Title: | Bildverarbeitung für die Medizin 2013 |
| DOI: | 10.1007/978-3-642-36480-8_56 |
| Abstract: | Automatic segmentation of medical images requires accurate detection of the desired organ as a first step. In contrast to application specific approaches, learning-based object detection algorithms are easily adaptable to new applications. We present a learning-based object detection approach based on the Viola-Jones algorithm. We propose several extensions to the original approach, including a new 3D feature type and a multi-organ detection scheme. The algorithm is used to detect six different organs in CT scans as well as the prostate in MRI data. Our evaluation shows that the algorithm provides fast and reliable detection results in all cases. |
| Uncontrolled Keywords: | Business Field: Visual decision support, Research Area: Confluence of graphics and vision, Medical image processing, Medical imaging, Object detection |
| 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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