Semi-automatic segmentation for 3D motion analysis of the tongue with dynamic MRI

• Published in: Computerized medical imaging and graphics Vol. 38; no. 8; pp. 714 - 724
• Main Authors: Lee, Junghoon, Woo, Jonghye, Xing, Fangxu, Murano, Emi Z., Stone, Maureen, Prince, Jerry L.
• Format: Journal Article
• Language: English
• Published: New York, NY Elsevier Ltd 01.12.2014; Elsevier
• Subjects: Algorithms; Applied sciences; Artificial intelligence; Biological and medical sciences; Computer science; control theory; systems; Data processing. List processing. Character string processing; Deformable registration; Deformation; Dynamic MRI; Dynamics; Exact sciences and technology; Frames; Humans; Image Interpretation, Computer-Assisted - methods; Imaging, Three-Dimensional - methods; Internal Medicine; Investigative techniques, diagnostic techniques (general aspects); Magnetic Resonance Imaging - methods; Medical sciences; Memory organisation. Data processing; Motion; Movement - physiology; Other; Otorhinolaryngology. Stomatology. Orbit; Pattern Recognition, Automated - methods; Pattern recognition. Digital image processing. Computational geometry; Radiodiagnosis. Nmr imagery. Nmr spectrometry; Random walker; Reproducibility of Results; Segmentation; Sensitivity and Specificity; Software; Speech; Speech - physiology; Subtraction Technique; Super-resolution reconstruction; Three dimensional; Tongue; Tongue - anatomy & histology; Tongue - physiology; Two dimensional; User-Computer Interface; Motion; Super-resolution reconstruction; Tongue; Segmentation; Dynamic MRI; Random walker; Deformable registration; Image registration; Computer vision; High resolution; Target tracking; Statistical analysis; Motion estimation; Similarity; Random walk; Variability; Nuclear magnetic resonance imaging; Tissue; Image segmentation; Tridimensional image; Automatic analysis; Mechanical deformation
• DOI: 10.1016/j.compmedimag.2014.07.004
• ISSN: 0895-6111; 1879-0771

•We proposed a segmentation method for dynamic MRI-based tongue motion analysis.•Proposed method requires a small amount of user-interactions.•Proposed method significantly reduces the segmentation time.•Proposed method produces more consistent segmentation than manual segmentation. Dynamic MRI has been widely used to track the motion of the tongue and measure its internal deformation during speech and swallowing. Accurate segmentation of the tongue is a prerequisite step to define the target boundary and constrain the tracking to tissue points within the tongue. Segmentation of 2D slices or 3D volumes is challenging because of the large number of slices and time frames involved in the segmentation, as well as the incorporation of numerous local deformations that occur throughout the tongue during motion. In this paper, we propose a semi-automatic approach to segment 3D dynamic MRI of the tongue. The algorithm steps include seeding a few slices at one time frame, propagating seeds to the same slices at different time frames using deformable registration, and random walker segmentation based on these seed positions. This method was validated on the tongue of five normal subjects carrying out the same speech task with multi-slice 2D dynamic cine-MR images obtained at three orthogonal orientations and 26 time frames. The resulting semi-automatic segmentations of a total of 130 volumes showed an average dice similarity coefficient (DSC) score of 0.92 with less segmented volume variability between time frames than in manual segmentations.