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Magana-Salgado U, Namburi P, Feigin-Almon M, Pallares-Lopez R, Anthony B. A comparison of point-tracking algorithms in ultrasound videos from the upper limb. Biomed Eng Online 2023; 22:52. [PMID: 37226240 DOI: 10.1186/s12938-023-01105-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Accepted: 04/25/2023] [Indexed: 05/26/2023] Open
Abstract
Tracking points in ultrasound (US) videos can be especially useful to characterize tissues in motion. Tracking algorithms that analyze successive video frames, such as variations of Optical Flow and Lucas-Kanade (LK), exploit frame-to-frame temporal information to track regions of interest. In contrast, convolutional neural-network (CNN) models process each video frame independently of neighboring frames. In this paper, we show that frame-to-frame trackers accumulate error over time. We propose three interpolation-like methods to combat error accumulation and show that all three methods reduce tracking errors in frame-to-frame trackers. On the neural-network end, we show that a CNN-based tracker, DeepLabCut (DLC), outperforms all four frame-to-frame trackers when tracking tissues in motion. DLC is more accurate than the frame-to-frame trackers and less sensitive to variations in types of tissue movement. The only caveat found with DLC comes from its non-temporal tracking strategy, leading to jitter between consecutive frames. Overall, when tracking points in videos of moving tissue, we recommend using DLC when prioritizing accuracy and robustness across movements in videos, and using LK with the proposed error-correction methods for small movements when tracking jitter is unacceptable.
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Affiliation(s)
- Uriel Magana-Salgado
- Department of Mechanical Engineering, MIT, Cambridge, MA, 02139, USA
- Mechanical Engineering Graduate Program, MIT, Cambridge, MA, 02139, USA
| | - Praneeth Namburi
- Institute for Medical Engineering and Science, Massachusetts Institute of Technology, 77 Massachusetts Ave, 12-3211, Cambridge, MA, 02139, USA.
- MIT.Nano Immersion Lab, MIT, Cambridge, MA, 02139, USA.
| | | | - Roger Pallares-Lopez
- Department of Mechanical Engineering, MIT, Cambridge, MA, 02139, USA
- Mechanical Engineering Graduate Program, MIT, Cambridge, MA, 02139, USA
| | - Brian Anthony
- Department of Mechanical Engineering, MIT, Cambridge, MA, 02139, USA
- Institute for Medical Engineering and Science, Massachusetts Institute of Technology, 77 Massachusetts Ave, 12-3211, Cambridge, MA, 02139, USA
- MIT.Nano Immersion Lab, MIT, Cambridge, MA, 02139, USA
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