Application of a novel Kalman filter based block matching method to ultrasound images for hand tendon displacement estimation

Lai, Te-Jen; Chen, Hsiao I.; Shih, Chuan Feng; Kuo, Li-Chieh; Hsu, Hsiu‐Yun; Huang, Chih-Chung

doi:10.1118/1.4937932

Cited by 8 publications

(5 citation statements)

References 20 publications

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“…2 . Displacement estimates were obtained using the Fisher–Tippett block-matching method 25 , with a Kalman-filter algorithm being subsequently applied to reduce tracking errors 26 . The parameter settings for the Fisher–Tippett block matching method are shown in Table 1 .…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

A Novel Adhesion Index for Verifying the Extent of Adhesion for the Extensor Digitorum Communis in Patients with Metacarpal Fractures

Lai

Chen

Shih

et al. 2016

Sci Rep

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This study aims to determine if the relative displacement between the extensor digitorum communis (EDC) tendon and its surrounding tissues can be used as an adhesion index (AI) for assessing adhesion in metacarpal fractures by comparing two clinical measures, namely single-digit-force and extensor lag (i.e., the difference between passive extension and full active extension). The Fisher–Tippett block-matching method and a Kalman-filter algorithm were used to determine the relative displacements in 39 healthy subjects and 8 patients with metacarpal fractures. A goniometer was used to measure the extensor lag, and a force sensor was used to measure the single-digit-force. Measurements were obtained twice for each patient to evaluate the performance of the AI in assessing the progress of rehabilitation. The Pearson correlation coefficient was calculated to quantify the various correlations between the AI, extensor lag, and single-digit-force. The results showed strong correlations between the AI and the extensor lag, the AI and the single-digit-force, and the extensor lag and the single-digit-force (r = 0.718, −0.849, and −0.741; P = 0.002, P < 0.001, and P = 0.001, respectively). The AI in the patients gradually decreased after continuous rehabilitation, but remained higher than that of healthy participants.

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Section: Methodsmentioning

confidence: 99%

“…The parameter settings for the Fisher–Tippett block matching method are shown in Table 1 . The parameter settings for the Kalman filter were the same as those applied in Lai 26 except that the additive white noise of R and the covariance matrix of the white sequence of Q were set at 1 and 0.005, respectively.…”

Section: Methodsmentioning

confidence: 99%

A Novel Adhesion Index for Verifying the Extent of Adhesion for the Extensor Digitorum Communis in Patients with Metacarpal Fractures

Lai

Chen

Shih

et al. 2016

Sci Rep

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“…The ability to track increasingly smaller regions can establish a general methodology for tracking deformable features. Region and point-tracking algorithms such as Optical Flow [ 18 , 19 ], block matching [ 20 , 21 ], and template tracking [ 22 ] have been used to identify and track various tissues, tendons, and bones. Optical Flow uses pixel intensity (brightness) changes between two consecutive frames to determine pixel velocity and displacements [ 16 ] which can be helpful to track slow-moving features in any video.…”

Section: Introductionmentioning

confidence: 99%

A comparison of point-tracking algorithms in ultrasound videos from the upper limb

Magana-Salgado,

Namburi,

Feigin-Almon

et al. 2023

BioMed Eng OnLine

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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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“…The block matching method is used widely for measuring the movement. [34][35][36] In our previous study, the movement of the heart wall was measured by the block matching method, and the velocities with minute vibrations at multiple points in the myocardium were obtained. 37,38) This method enables movements to be tracked by applying the cross-correlation method to the speckle pattern within a region of interest (ROI) in successive frames.…”

Section: Introductionmentioning

confidence: 99%

Local two-dimensional distribution of propagation speed of myocardial contraction for ultrasonic visualization of contraction propagation

Hayashi

Mori

Arakawa

et al. 2019

Jpn. J. Appl. Phys.

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The propagation of myocardial contraction caused by the conduction of electrical excitation in the heart has been visualized in our previous study. However, it was assumed that the contraction propagated parallel to the heart wall and the propagation speed was constant within the measurement area. In the present study, we estimated the two-dimensional propagation speed of contraction at each local area by ultrasonic measurement, and examined the mechanism of the contraction propagation in the heart by calculating the spatial distribution of the propagation speed vectors. By applying the proposed method to the interventricular septum of the human heart, the propagation speed in the lateral direction was approximately 1.6 times faster than that in the beam direction. The significant difference in propagation speeds between the specialized and ordinary myocardia was detected successfully. This study suggests that the proposed method can detect the myocardial ischemic and arrhythmia regions non-invasively.

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Application of a novel Kalman filter based block matching method to ultrasound images for hand tendon displacement estimation

Abstract: The obtained results show the potential for applying the proposed FT-K1 method in clinical applications for evaluating the tendon injury level after metacarpal fractures and assessing the recovery of an injured tendon during rehabilitation.

Cited by 8 publications

References 20 publications

A Novel Adhesion Index for Verifying the Extent of Adhesion for the Extensor Digitorum Communis in Patients with Metacarpal Fractures

A Novel Adhesion Index for Verifying the Extent of Adhesion for the Extensor Digitorum Communis in Patients with Metacarpal Fractures

A comparison of point-tracking algorithms in ultrasound videos from the upper limb

Local two-dimensional distribution of propagation speed of myocardial contraction for ultrasonic visualization of contraction propagation

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