Localization of skeletal and aortic landmarks in trauma CT data based on the discriminative generalized Hough transform

Cristian Lorenz; Eberhard Hansis; Jürgen Weese; Heike Carolus

doi:10.1117/12.2216251

21 March 2016 Localization of skeletal and aortic landmarks in trauma CT data based on the discriminative generalized Hough transform

Cristian Lorenz, Eberhard Hansis, Jürgen Weese, Heike Carolus

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Proceedings Volume 9784, Medical Imaging 2016: Image Processing; 978420 (2016) https://doi.org/10.1117/12.2216251
Event: SPIE Medical Imaging, 2016, San Diego, California, United States

Abstract

Computed tomography is the modality of choice for poly-trauma patients to assess rapidly skeletal and vascular integrity of the whole body. Often several scans with and without contrast medium or with different spatial resolution are acquired. Efficient reading of the resulting extensive set of image data is vital, since it is often time critical to initiate the necessary therapeutic actions. A set of automatically found landmarks can facilitate navigation in the data and enables anatomy oriented viewing. Following this intention, we selected a comprehensive set of 17 skeletal and 5 aortic landmarks. Landmark localization models for the Discriminative Generalized Hough Transform (DGHT) were automatically created based on a set of about 20 training images with ground truth landmark positions. A hierarchical setup with 4 resolution levels was used. Localization results were evaluated on a separate test set, consisting of 50 to 128 images (depending on the landmark) with available ground truth landmark locations. The image data covers a large amount of variability caused by differences of field-of-view, resolution, contrast agent, patient gender and pathologies. The median localization error for the set of aortic landmarks was 14.4 mm and for the set of skeleton landmarks 5.5 mm. Median localization errors for individual landmarks ranged from 3.0 mm to 31.0 mm. The runtime performance for the whole landmark set is about 5s on a typical PC.

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Cristian Lorenz, Eberhard Hansis, Jürgen Weese, and Heike Carolus "Localization of skeletal and aortic landmarks in trauma CT data based on the discriminative generalized Hough transform", Proc. SPIE 9784, Medical Imaging 2016: Image Processing, 978420 (21 March 2016); https://doi.org/10.1117/12.2216251

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KEYWORDS

Data modeling

Adaptive optics

Hough transforms

Image resolution

Computed tomography

Head

Image segmentation

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