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Conference Papers Year : 2020

Unsupervised segmentation of stents corrupted by artifacts in medical X-ray images

Abstract

We propose a new methodology for the segmentation of stents in 3D X-ray acquisitions. Such data are often corrupted by strong artifacts around the stent, requiring the development of a robust algorithm: because of the medical application, we need to produce an accurate segmentation. Moreover, we aim at developping a robust technique that can handle heterogeneous data. We propose a two-step, coarse-to-fine approach, that handles the corrupted cases. This approach leads to better results illustrated in the context of metallic artefact reduction.
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Dates and versions

hal-03122418 , version 1 (08-04-2022)

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Hugo Gangloff, Emmanuel Monfrini, Christophe Collet, Nabil Chakfe. Unsupervised segmentation of stents corrupted by artifacts in medical X-ray images. IPTA 2020: 10th international conference on Image Processing Theory, Tools and Applications, Nov 2020, Paris, France. pp.1-6, ⟨10.1109/IPTA50016.2020.9286660⟩. ⟨hal-03122418⟩
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