Abstract
Ultrasound imaging is a very versatile and fast medical imaging modality, however it can suffer from serious image quality degradation. The origin of such loss of image quality is often difficult to identify in detail, therefore it makes it difficult to design probes and tools that are less impacted. The objective of this manuscript is to present an end-to-end simulation pipeline that makes it possible to generate synthetic ultrasound images while controlling every step of the pipeline, from the simulated cardiac function, to the torso anatomy, probe parameters, and reconstruction process. Such a pipeline enables to vary every parameter in order to quantitatively evaluate its impact on the final image quality. We present here first results on classical ultrasound phantoms and a digital heart. The utility of this pipeline is exemplified with the impact of ribs on the resulting cardiac ultrasound image.
A. Legay and T. Tiennot—Co-first authors, they contributed equally to this work.
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Legay, A., Tiennot, T., Gelly, JF., Sermesant, M., Bulté, J. (2020). End-to-end Cardiac Ultrasound Simulation for a Better Understanding of Image Quality. In: Pop, M., et al. Statistical Atlases and Computational Models of the Heart. Multi-Sequence CMR Segmentation, CRT-EPiggy and LV Full Quantification Challenges. STACOM 2019. Lecture Notes in Computer Science(), vol 12009. Springer, Cham. https://doi.org/10.1007/978-3-030-39074-7_18
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DOI: https://doi.org/10.1007/978-3-030-39074-7_18
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