Temporal Super Resolution Enhancement of Echocardiographic Images Based on Sparse Representation

Gifani, Parisa; Behnam, Hamid; Haddadi, Farzan; Sani, Zahra Alizadeh; Shojaeifard, Maryam

doi:10.1109/tuffc.2015.2493881

Cited by 22 publications

(7 citation statements)

References 54 publications

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“…All state-of-the-art approaches for the frame rate improvement is either acquisition-based (hardware) or postprocessing (software). [48][49][50][51][52][53][54] However, most of these approaches may have a higher frame rate improvement than the suggested approach. It can be seen that direct comparison with these approaches is not practically logical.…”

Section: Discussionmentioning

confidence: 99%

Compressive sensing theory and neighborhood spatial‐temporal information for frame rate improvement of dynamic ultrasonic imaging

Hosseinpour

Behnam

Shojaeifard

2020

Int J Imaging Syst Tech

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The frame rate improvement is an essential issue in dynamic ultrasonic imaging for better displaying rapid heart movements. In this study, a new technique using the compressive sensing (CS) theory was introduced for the frame rate improvement of two-dimensional (2D) and three-dimensional (3D) dynamic ultrasonic imaging. In the suggested procedure, a fewer radio frequency (RF) lines were received. Subsequently, the CS theory by the recommended approach was used to reconstruct the nonacquired RF lines. The suggested process uses the temporal and spatial information in the neighborhood samples of the desired sample in RF frame sequences. We utilized the dictionary learning technique to construct the sparsifying over-complete dictionary. Here, we used the 2D in vivo carotid artery data and the 3D simulated echocardiography for the quality assessment of the suggested approach. According to the qualitative and quantitative results, reconstructions in the suggested approach are more precise, and the reconstruction errors are much lower than the conventional techniques. The tissues' structure in reconstructed videos by the suggested approach is preserved to be applicable for medical diagnosis goals. The frame rate can be improved by a factor of 10 with suitable quality for medical diagnosis goals. The implementation of the suggested approach does not require any more hardware or alternation in the devices' available hardware.The frame rate can be improved by only implementing effective programming on the ultrasound systems.

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Section: Discussionmentioning

confidence: 99%

Compressive sensing theory and neighborhood spatial‐temporal information for frame rate improvement of dynamic ultrasonic imaging

Hosseinpour

Behnam

Shojaeifard

2020

Int J Imaging Syst Tech

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“…In this article, the SR principle is employed. Recently, the SR-based method is widely used for object detection [27]- [29], [33], [34], image enhancement [35], [36], and classification [37]- [39]. The SR principle can be explained as a given set of input data, and it can be combined with a few linear elements from a set of representation patterns.…”

Section: Basic Concepts Of Srmentioning

confidence: 99%

Small Sample Set Inshore Ship Detection From VHR Optical Remote Sensing Images Based on Structured Sparse Representation

Zhuang

Chen³

2020

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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Inshore ship detection from very high resolution (VHR) optical remote sensing images has been playing a critical role in various civil and military applications. However, it brings up an important challenge, which is difficult to complete effective and robust feature extraction when valid inshore ship training sample acquired is limited, and the severe imbalance problem exists of positive and negative samples. In order to tackle the abovementioned difficulties, the structured sparse representation model (SSRM) is proposed to achieve inshore ship detection in more effectively and robustly way by circumstances of the small sample set. Here, SSRM has two steps that include inshore ship region proposal (RP) and orientation prediction (OP). Related to the RP process, the error matrix embedded in SSRM not only prevents to build the high-dimension background subdictionary and imbalance problem of positive and negative samples, but also achieves an effective intraclass robustness description of inshore ships and background. For the OP stage, the low-rank constraint of common sharing atoms in SSRM can make inshore ship direction be extracted by their sparse coding. In addition, based on RP and OP guidance, the proposed comprehensive structure voting can achieve an accurate contour detection of inshore ships. Finally, several experimental results employ that Google Earth service, HRSC 2016, and DOTA datasets proved the effectiveness of the proposed method. The results show that proposed inshore ship detection method can provide approximately 83.7% Recall and 72.3% Precision by using only over 100 positive training samples, which outperforms the state of the art methods.

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“…However, this frame rate is not adequate for the study of fast‐moving objects in for example fetus and small animal echocardiographic imaging. Hence, a higher frame rate (2‐3 times) and full‐view ultrasound imaging method is required 24 . So, Increasing the frame rate by two or three times is sufficient for proper diagnosis in echocardiography.…”

Section: Introductionmentioning

confidence: 99%

A fast and high frame rate adaptive beamforming using DCT‐based RF‐line recovery in line‐by‐line ultrasound imaging

Afrakhteh

Behnam

2020

Int J Imaging Syst Tech

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Ultrasound imaging is an important modality used in medical imaging. One of the significant stages in the ultrasound imaging is the beamforming process. This article proposes a new technique for reducing the overall computational time of adaptive linear ultrasound imaging. The method uses the discrete cosine transform‐based reconstruction for missing data imputation. The novelty of the paper is that we do not need to beam‐form the total scan lines, so the time of image construction can be saved significantly. In other words, a fraction of the total scan lines is selected for beamforming and the others are assumed to have values as Not‐a‐Number (NaN). The proposed reconstruction technique tries to assign appropriate values to the NaN ones. We applied the proposed method to the simulated and experimental radio frequency (RF) datasets for resolution and contrast evaluation. Results showed that the proposed technique is near to the minimum variance (MV) method in terms of resolution and contrast, and has less computational time for image formation compared to the MV. As some quantitative examples in some experiments we have formed only 50% and 33% of the total lines and reconstructed the rest, then we have been able to increase the frame rate twice and three times, respectively, which can be very useful in many applications, especially in echocardiography imaging. In addition, since the execution time of the reconstruction algorithm is not very significant, we were also able to increase the speed by two and three times while achieving an error of less than 10% compared to the case of using all image lines.

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Temporal Super Resolution Enhancement of Echocardiographic Images Based on Sparse Representation

Cited by 22 publications

References 54 publications

Compressive sensing theory and neighborhood spatial‐temporal information for frame rate improvement of dynamic ultrasonic imaging

Compressive sensing theory and neighborhood spatial‐temporal information for frame rate improvement of dynamic ultrasonic imaging

Small Sample Set Inshore Ship Detection From VHR Optical Remote Sensing Images Based on Structured Sparse Representation

A fast and high frame rate adaptive beamforming using DCT‐based RF‐line recovery in line‐by‐line ultrasound imaging

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