Abstract
The segmentation of the anterior fascia of the rectus abdominis muscle is an important step towards the analysis of abdominal vasculature. It may advance Computer Aided Detection tools that support the activity of clinicians who study vessels for breast reconstruction using the Deep Inferior Epigastric Perforator flap. In this paper, we propose a two-fold methodology to detect the anterior fascia in Computerized Tomographic Angiography volumes. First, a slice-wise thresholding is applied and followed by a post-processing phase. Finally, an interpolation framework is used to obtain a final smooth fascia detection. We evaluated our method in 20 different volumes, by calculating the mean Euclidean distance to manual annotations, achieving subvoxel error.
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Acknowledgments
This work was funded by the Project “NanoSTIMA: Macro–to–Nano Human Sensing: Towards Integrated Multimodal Health Monitoring and Analytics/NORTE–01–0145–FEDER–000016” financed by the North Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, and through the European Regional Development Fund (ERDF), and also by Fundação para a Ciência e a Tecnologia (FCT) within Ph.D grant number SFRH/BD/126224/2016.
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Araújo, R.J., Oliveira, H.P. (2017). Segmentation of the Rectus Abdominis Muscle Anterior Fascia for the Analysis of Deep Inferior Epigastric Perforators. In: Alexandre, L., Salvador Sánchez, J., Rodrigues, J. (eds) Pattern Recognition and Image Analysis. IbPRIA 2017. Lecture Notes in Computer Science(), vol 10255. Springer, Cham. https://doi.org/10.1007/978-3-319-58838-4_59
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DOI: https://doi.org/10.1007/978-3-319-58838-4_59
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