UltraTimTrack

UltraTimTrack applies a Kalman filter to combine fascicle length and fascicle angle estimates from UltraTrack and TimTrack algorithms into a hybrid algorithm for tracking muscle fascicles in B-mode ultrasound image sequences.

Key Features:

• Kalman-filter-based hybrid algorithm: Combines estimates from UltraTrack and TimTrack algorithms to produce low-noise, drift-free fascicle tracking.
• Low-noise estimation: Achieves cycle-to-cycle variability of 1.4 +/- 0.4 mm for fascicle length and 0.6 +/- 0.3 deg for fascicle angle, comparable to UltraTrack and lower than TimTrack.
• Drift-free tracking: Accumulated deviations over 120 cyclical contractions are 2.1 +/- 1.3 mm for fascicle length and 0.8 +/- 0.7 deg for fascicle angle, comparable to TimTrack and substantially lower than UltraTrack.
• Robustness across conditions: Less affected by experimental conditions and image acquisition settings than its parent algorithms UltraTrack and TimTrack.
• Fast processing: Processing time of 0.2 s per image, at least five times shorter than recently-proposed hybrid and DL_Track algorithms.

Scientific Applications:

• Skeletal muscle architecture analysis: Tracks muscle fascicle length and fascicle angle changes during cyclical submaximal plantar flexion contractions and passive ankle joint rotations.
• Medial gastrocnemius imaging: Quantifies muscle architectural changes from B-mode ultrasound image sequences of the human medial gastrocnemius.
• Muscle function interpretation: Provides estimates of muscle architectural changes to inform interpretations of muscle function during movement.

Methodology:

UltraTimTrack applies a Kalman filter to combine fascicle length and fascicle angle estimates from existing UltraTrack and TimTrack algorithms. The algorithm was validated using ultrasound image sequences collected from the human medial gastrocnemius of healthy individuals performing cyclical submaximal plantar flexion contractions or remaining at rest during passive ankle joint rotations at given frequencies and amplitudes whilst seated in a dynamometer chair. Tracking accuracy, noise, and drift were quantified as mean, cycle-to-cycle variability, and accumulated between-contraction variability in fascicle length and fascicle angle.