Kirschner, Matthias ; Jung, Florian ; Wesarg, Stefan (2012)
Automatic Prostate Segmentation in MR Images with a Probabilistic Active Shape Model.
PROMISE12. Proceedings.
Conference or Workshop Item, Bibliographie
Abstract
Segmentation of the prostate gland in Magnetic Resonance (MR) images is an important task for image-guided prostate cancer therapy. The low contrast of the prostate to surrounding tissue in MR images makes automatic segmentation very challenging. In this paper, we propose an automatic approach for robust and accurate prostate segmentation in T2-weighted MR scans. We first employ a boosted prostate detector to locate the prostate in the images, and then use a Probabilistic Active Shape Model for the delineation of its contour. Our approach has been quantitatively evaluated on 50 MR images, on which we achieve a median dice coefficient of 0.85 (IQR: 0.09).
| Item Type: | Conference or Workshop Item |
|---|---|
| Erschienen: | 2012 |
| Creators: | Kirschner, Matthias ; Jung, Florian ; Wesarg, Stefan |
| Type of entry: | Bibliographie |
| Title: | Automatic Prostate Segmentation in MR Images with a Probabilistic Active Shape Model |
| Language: | English |
| Date: | 2012 |
| Event Title: | PROMISE12. Proceedings |
| Abstract: | Segmentation of the prostate gland in Magnetic Resonance (MR) images is an important task for image-guided prostate cancer therapy. The low contrast of the prostate to surrounding tissue in MR images makes automatic segmentation very challenging. In this paper, we propose an automatic approach for robust and accurate prostate segmentation in T2-weighted MR scans. We first employ a boosted prostate detector to locate the prostate in the images, and then use a Probabilistic Active Shape Model for the delineation of its contour. Our approach has been quantitatively evaluated on 50 MR images, on which we achieve a median dice coefficient of 0.85 (IQR: 0.09). |
| Uncontrolled Keywords: | Forschungsgruppe Medical Computing (MECO), Business Field: Visual decision support, Research Area: Confluence of graphics and vision, Active shape models (ASM), Segmentation, Object detection, Magnetic resonance imaging (MRI) |
| 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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