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Multi-Channel Volumetric Neural Network for Knee Cartilage Segmentation in Cone-Beam CT

Maier J, Rivera Monroy L, Syben-Leisner C, Jeon Y, Choi JH, Hall M, Levenston M, Gold G, Fahrig R, Maier A (2020)

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Publication Type: Book chapter / Article in edited volumes

Publication year: 2020

Journal

Publisher: Springer Vieweg

Edited Volumes: Bildverarbeitung für die Medizin 2020

Series: Informatik aktuell

City/Town: Wiesbaden

Pages Range: 67-72

ISBN: 9783658292669

DOI: 10.1007/978-3-658-29267-6_14

Abstract

Analyzing knee cartilage thickness and strain under load can help to further the understanding of the effects of diseases like Osteoarthritis. A precise segmentation of the cartilage is a necessary prerequisite for this analysis. This segmentation task has mainly been addressed in Magnetic Resonance Imaging, and was rarely investigated on contrast-enhanced Computed Tomography, where contrast agent visualizes the border between femoral and tibial cartilage. To overcome the main drawback of manual segmentation, namely its high time investment, we propose to use a 3D Convolutional Neural Network for this task. The presented architecture consists of a V-Net with SeLu activation, and a Tversky loss function. Due to the high imbalance between very few cartilage pixels and many background pixels, a high false positive rate is to be expected. To reduce this rate, the two largest segmented point clouds are extracted using a connected component analysis, since they most likely represent the medial and lateral tibial cartilage surfaces. The resulting segmentations are compared to manual segmentations, and achieve on average a recall of 0.69, which confirms the feasibility of this approach.

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How to cite

APA:

Maier, J., Rivera Monroy, L., Syben-Leisner, C., Jeon, Y., Choi, J.-H., Hall, M.,... Maier, A. (2020). Multi-Channel Volumetric Neural Network for Knee Cartilage Segmentation in Cone-Beam CT. In Thomas Tolxdorff, Thomas M. Deserno, Heinz Handels, Andreas Maier, Klaus H. Maier-Hein, Christoph Palm (Eds.), Bildverarbeitung für die Medizin 2020. (pp. 67-72). Wiesbaden: Springer Vieweg.

MLA:

Maier, Jennifer, et al. "Multi-Channel Volumetric Neural Network for Knee Cartilage Segmentation in Cone-Beam CT." Bildverarbeitung für die Medizin 2020. Ed. Thomas Tolxdorff, Thomas M. Deserno, Heinz Handels, Andreas Maier, Klaus H. Maier-Hein, Christoph Palm, Wiesbaden: Springer Vieweg, 2020. 67-72.

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