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Motion estimation using the firefly algorithm in ultrasonic image sequence of soft tissue.

Chao CF, Horng MH, Chen YC - Comput Math Methods Med (2015)

Bottom Line: These images usually have a low signal-to-noise ratio presentation.The phenomenon gives rise to traditional motion estimation algorithms that are not suitable to measure the motion vectors.The experimental results show that the IFA can assess the vector with better efficiency and almost equal estimation quality compared to the traditional IFSA method.

View Article: PubMed Central - PubMed

Affiliation: Department of Computer Science and Information Engineering, National Pingtung University, No. 4-18, Minsheng Road, Pingtung 90003, Taiwan.

ABSTRACT
Ultrasonic image sequence of the soft tissue is widely used in disease diagnosis; however, the speckle noises usually influenced the image quality. These images usually have a low signal-to-noise ratio presentation. The phenomenon gives rise to traditional motion estimation algorithms that are not suitable to measure the motion vectors. In this paper, a new motion estimation algorithm is developed for assessing the velocity field of soft tissue in a sequence of ultrasonic B-mode images. The proposed iterative firefly algorithm (IFA) searches for few candidate points to obtain the optimal motion vector, and then compares it to the traditional iterative full search algorithm (IFSA) via a series of experiments of in vivo ultrasonic image sequences. The experimental results show that the IFA can assess the vector with better efficiency and almost equal estimation quality compared to the traditional IFSA method.

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Illustration of the block-matching algorithm [18].
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fig1: Illustration of the block-matching algorithm [18].

Mentions: Because of its simplicity, the block-matching is a widely used algorithm in motion estimation. In matching procedures, the estimated image block of the processing frame will correspond to the best matching location within the predefined search window of the reference frame, as shown in Figure 1. In general, the size of estimated block,  B is  n × n  pixels and the size of the corresponding search window S is (2W + 1) × (2W + 1). These two windows are centered at the same point  (x, y)  in the two consecutive image frames (fk−1  and  fk). The full search searches for all possible locations within the search window by evaluating some matching criteria and selected one location  (x′, y′)  of the corresponding block  B*. The relative displacement of the two locations of both  (x, y)  and (x′, y′) is defined as the motion vector,  uB = (uBx, uBy),  uBx = x′ − x, uBy = y′ − y.


Motion estimation using the firefly algorithm in ultrasonic image sequence of soft tissue.

Chao CF, Horng MH, Chen YC - Comput Math Methods Med (2015)

Illustration of the block-matching algorithm [18].
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4383159&req=5

fig1: Illustration of the block-matching algorithm [18].
Mentions: Because of its simplicity, the block-matching is a widely used algorithm in motion estimation. In matching procedures, the estimated image block of the processing frame will correspond to the best matching location within the predefined search window of the reference frame, as shown in Figure 1. In general, the size of estimated block,  B is  n × n  pixels and the size of the corresponding search window S is (2W + 1) × (2W + 1). These two windows are centered at the same point  (x, y)  in the two consecutive image frames (fk−1  and  fk). The full search searches for all possible locations within the search window by evaluating some matching criteria and selected one location  (x′, y′)  of the corresponding block  B*. The relative displacement of the two locations of both  (x, y)  and (x′, y′) is defined as the motion vector,  uB = (uBx, uBy),  uBx = x′ − x, uBy = y′ − y.

Bottom Line: These images usually have a low signal-to-noise ratio presentation.The phenomenon gives rise to traditional motion estimation algorithms that are not suitable to measure the motion vectors.The experimental results show that the IFA can assess the vector with better efficiency and almost equal estimation quality compared to the traditional IFSA method.

View Article: PubMed Central - PubMed

Affiliation: Department of Computer Science and Information Engineering, National Pingtung University, No. 4-18, Minsheng Road, Pingtung 90003, Taiwan.

ABSTRACT
Ultrasonic image sequence of the soft tissue is widely used in disease diagnosis; however, the speckle noises usually influenced the image quality. These images usually have a low signal-to-noise ratio presentation. The phenomenon gives rise to traditional motion estimation algorithms that are not suitable to measure the motion vectors. In this paper, a new motion estimation algorithm is developed for assessing the velocity field of soft tissue in a sequence of ultrasonic B-mode images. The proposed iterative firefly algorithm (IFA) searches for few candidate points to obtain the optimal motion vector, and then compares it to the traditional iterative full search algorithm (IFSA) via a series of experiments of in vivo ultrasonic image sequences. The experimental results show that the IFA can assess the vector with better efficiency and almost equal estimation quality compared to the traditional IFSA method.

Show MeSH
Related in: MedlinePlus