Abstract #2776
Regional Achilles Tendon Segmentation for Quantitative Magnetic Resonance Imaging at 1.5 Tesla
Dominik Vilimek1, Radana Kahankova1, Radek Martinek1, Martin Kryl1, Veronika Janacova2, Milos Golian3,4, Jaroslav Uchytil3, Pavla Hanzlikova5,6, Pavol Szomolanyi2,7, Siegfried Trattnig2,8,9,10, and Vladimir Juras2
1Department of Cybernetics and Biomedical Engineering, VSB Technical University of Ostrava, Ostrava, Czech Republic, 2Department of Biomedical Imaging and Image-guided Therapy, High Field MR Centre, Medical University of Vienna, Vienna, Austria, 3Department of Human Movement Studies, Human Motion Diagnostic Center, University of Ostrava, Ostrava, Czech Republic, 4Department of Radiology, Vitkovice Hospital, Ostrava, Czech Republic, 5Department of Imaging Methods, Faculty of Medicine, University of Ostrava, Ostrava, Czech Republic, 6Department of Radiology, University Hospital Ostrava, Ostrava, Czech Republic, 7Institute of Measurement Science, Slovak Academy of Sciences, Bratislava, Slovakia, 8CD Laboratory fo MR Imaging Biomarkers (BIOMAK), Vienna, Austria, 9Austrian Cluster for Tissue Regeneration, Ludwig Boltzmann Institute for Experimental and Clinical Traumatology, Vienna, Austria, 10Institute for Clinical Molecular MRI in the Musculoskeletal System, Karl Landsteiner Society, Vienna, Austria
Synopsis
Keywords: Tendon/Ligament, Machine Learning/Artificial IntelligenceChanges in the Achilles tendon composition are associated with an increased risk of tendinopathy which is common in middle-aged overweight patients and is one of the most common sports injuries. However, measuring and quantifying such properties is a challenging task. The purpose of this paper is to introduce an end-to-end pipeline for segmenting Achilles tendon using deep convolutional neural networks and automatic segmentation into three segments. Our model shows promising results outperforming state-of-the-art approaches (Dice 90.6% and Jaccard 84.0%). This is one of the key steps for short and long T2* value analysis from 1.5T data.
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