UltraTrack: Software for semi-automated tracking of muscle fascicles in sequences of B-mode ultrasound images. Issue 128 (May 2016)

• Record Type: Journal Article
• Authors: Farris, Dominic James; Lichtwark, Glen A.
• Is Part Of: Computer methods and programs in biomedicine. Issue 128(2016)
• Page Start: 111
• Page End: 118
• Publication Date: 2016-05
• Subjects: Fascicle -- Tracking -- Ultrasound -- Automated -- Affine optic flow -- Matlab; Medicine -- Computer programs -- Periodicals; Biology -- Computer programs -- Periodicals; Computers -- Periodicals; Medicine -- Periodicals; Médecine -- Logiciels -- Périodiques; Biologie -- Logiciels -- Périodiques; Biology -- Computer programs; Medicine -- Computer programs; Periodicals; Electronic journals; 610.28
• DOI: 10.1016/j.cmpb.2016.02.016
• Languages: English
• ISSNs: 0169-2607

Abstract

Highlights: We have developed a freely available software package for semi-automated tracking of muscle fascicles in B-mode ultrasound image sequences. Includes features to track multiple fascicles in multiple regions of the image and to correct for measurement drift with time. The software is available for Windows and MacOS as a standalone program or source code. Abstract: Background: Dynamic measurements of human muscle fascicle length from sequences of B-mode ultrasound images have become increasingly prevalent in biomedical research. Manual digitisation of these images is time consuming and algorithms for automating the process have been developed. Here we present a freely available software implementation of a previously validated algorithm for semi-automated tracking of muscle fascicle length in dynamic ultrasound image recordings, "UltraTrack". Methods: UltraTrack implements an affine extension to an optic flow algorithm to track movement of the muscle fascicle end-points throughout dynamically recorded sequences of images. The underlying algorithm has been previously described and its reliability tested, but here we present the software implementation with features for: tracking multiple fascicles in multiple muscles simultaneously; correcting temporal drift in measurements; manually adjusting tracking results; saving and re-loading of tracking results and loading a range of file formats. Results: Two example runs of the software are presented detailing the tracking of fascicles from several lower limb muscles during a squatting and walking activity. Conclusion: We have presented a software implementation of a validated fascicle-tracking algorithm and made the source code and standalone versions freely available for download.