Semantic segmentation of individual muscle groups in 3D thigh MRI

Azubuike Okorie; Sokratis Makrogiannis; Richard Spencer; Rita Kalyani; Luigi Ferrucci

doi:10.1117/12.2654507

3 April 2023 Semantic segmentation of individual muscle groups in 3D thigh MRI

Azubuike Okorie, Sokratis Makrogiannis, Richard Spencer, Rita Kalyani, Luigi Ferrucci

Author Affiliations +

Proceedings Volume 12464, Medical Imaging 2023: Image Processing; 124643D (2023) https://doi.org/10.1117/12.2654507
Event: SPIE Medical Imaging, 2023, San Diego, California, United States

Conference Poster

Abstract

We introduce a multi-atlas-based image segmentation (MAIS) framework for the four functional muscle groups, gracilis, hamstring, quadriceps femoris, and sartorius, of the left and right thighs, using 3D chemical shift encoding-based MRI scans obtained from the MyoSegmenTUM database. We generated a statistical atlas and its silver truth by statistical approaches and employed block-matching and 3D filtering (BM3D) to deblur the statistical atlas. We segmented the four pairs of the functional muscle groups of the thigh using three templates, including the statistical atlas, and fused the labels using STAPLE. We validated the performance of our method by calculating the Dice similarity coefficient (DSC) between the delineated muscle group and its ground truth. We also compared the performance of four deformable models: free-form deformation (FFD), two versions of symmetric normalization (SYN and SYNO), and symmetric diffeomorphic demons (SDD). Our results show that SDD with STAPLE produced a mean DSC of 0.784 over all muscle groups. These results imply that the proposed technique has great potential for quantification and characterization of individual muscle groups.

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Azubuike Okorie, Sokratis Makrogiannis, Richard Spencer, Rita Kalyani, and Luigi Ferrucci "Semantic segmentation of individual muscle groups in 3D thigh MRI", Proc. SPIE 12464, Medical Imaging 2023: Image Processing, 124643D (3 April 2023); https://doi.org/10.1117/12.2654507

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