Steger, Sebastian ; Bozoglu, Y. Nazli ; Kuijper, Arjan ; Wesarg, Stefan (2013)
Application of Radial Ray Based Segmentation to Cervical Lymph Nodes in CT Images.
In: IEEE Transactions on Medical Imagaing, 32 (5)
doi: 10.1109/TMI.2013.2242901
Article, Bibliographie
Abstract
The 3D-segmentation of lymph nodes in CT images is required for staging and disease progression monitoring. Major challenges are shape and size variance, as well as low contrast, image noise, and pathologies. In this paper, radial ray based segmentation is applied to lymph nodes: From a seed point, rays are cast into all directions and an optimization technique determines a radius for each ray based on image appearance and shape knowledge. Lymph node specific appearance cost functions are introduced and their optimal parameters are determined. For the first time, the resulting segmentation accuracy of different appearance cost functions and optimization strategies are compared. Further contributions are extensions to reduce the dependency on the seed point, to support a larger variety of shapes, and to enable interaction. The best results are obtained using graph-cut on a combination of the direction weighted image gradient and accumulated intensities outside a predefined intensity range. Evaluation on 100 lymph nodes shows that with an average symmetric surface distance of 0.41 mm the segmentation accuracy is close to manual segmentation and outperforms existing radial ray and model based methods. The method's inter-observer-variability of 5.9 for volume assessment is lower than the 15.9 obtained using manual segmentation.
Item Type: | Article |
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Erschienen: | 2013 |
Creators: | Steger, Sebastian ; Bozoglu, Y. Nazli ; Kuijper, Arjan ; Wesarg, Stefan |
Type of entry: | Bibliographie |
Title: | Application of Radial Ray Based Segmentation to Cervical Lymph Nodes in CT Images |
Language: | English |
Date: | 2013 |
Journal or Publication Title: | IEEE Transactions on Medical Imagaing |
Volume of the journal: | 32 |
Issue Number: | 5 |
DOI: | 10.1109/TMI.2013.2242901 |
Abstract: | The 3D-segmentation of lymph nodes in CT images is required for staging and disease progression monitoring. Major challenges are shape and size variance, as well as low contrast, image noise, and pathologies. In this paper, radial ray based segmentation is applied to lymph nodes: From a seed point, rays are cast into all directions and an optimization technique determines a radius for each ray based on image appearance and shape knowledge. Lymph node specific appearance cost functions are introduced and their optimal parameters are determined. For the first time, the resulting segmentation accuracy of different appearance cost functions and optimization strategies are compared. Further contributions are extensions to reduce the dependency on the seed point, to support a larger variety of shapes, and to enable interaction. The best results are obtained using graph-cut on a combination of the direction weighted image gradient and accumulated intensities outside a predefined intensity range. Evaluation on 100 lymph nodes shows that with an average symmetric surface distance of 0.41 mm the segmentation accuracy is close to manual segmentation and outperforms existing radial ray and model based methods. The method's inter-observer-variability of 5.9 for volume assessment is lower than the 15.9 obtained using manual segmentation. |
Uncontrolled Keywords: | Business Field: Digital society, Research Area: Confluence of graphics and vision, Computed tomography (CT), Image segmentation, Graph cuts |
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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