Improvement in Multi-Angle Plane Wave Image Quality Using Minimum Variance Beamforming with Adaptive Signal Coherence
For ultrasound multi-angle plane wave (PW) imaging, the coherent PW compounding (CPWC) method provides limited image quality because of its conventional delay-and-sum beamforming. The delay-multiply-and-sum (DMAS) method is a coherence-based algorithm that improves image quality by introducing signa...
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MDPI AG
2024-01-01
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| Online Access: | https://www.mdpi.com/1424-8220/24/1/262 |
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| author | Che-Chou Shen Chun-Lin Huang |
| author_facet | Che-Chou Shen Chun-Lin Huang |
| author_sort | Che-Chou Shen |
| collection | DOAJ |
| description | For ultrasound multi-angle plane wave (PW) imaging, the coherent PW compounding (CPWC) method provides limited image quality because of its conventional delay-and-sum beamforming. The delay-multiply-and-sum (DMAS) method is a coherence-based algorithm that improves image quality by introducing signal coherence among either receiving channels or PW transmit angles into the image output. The degree of signal coherence in DMAS is conventionally a global value for the entire image and thus the image resolution and contrast in the target region improves at the cost of speckle quality in the background region. In this study, the adaptive DMAS (ADMAS) is proposed such that the degree of signal coherence relies on the local characteristics of the image region to maintain the background speckle quality and the corresponding contrast-to-noise ratio (CNR). Subsequently, the ADMAS algorithm is further combined with minimum variance (MV) beamforming to increase the image resolution. The optimal MV estimation is determined to be in the direction of the PW transmit angle (Tx) for multi-angle PW imaging. Our results show that, using the PICMUS dataset, TxMV-ADMAS beamforming significantly improves the image quality compared with CPWC. When the <i>p</i> value is globally fixed to 2 as in conventional DMAS, though the main-lobe width and the image contrast in the experiments improve from 0.57 mm and 27.0 dB in CPWC, respectively, to 0.24 mm and 38.0 dB, the corresponding CNR decreases from 12.8 to 11.3 due to the degraded speckle quality. With the proposed ADMAS algorithm, however, the adaptive <i>p</i> value in DMAS beamforming helps to restore the CNR value to the same level of CPWC while the improvement in image resolution and contrast remains evident. |
| first_indexed | 2024-03-08T14:57:53Z |
| format | Article |
| id | doaj.art-f642874a5f234acbab9f4ac6597d94d2 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-08T14:57:53Z |
| publishDate | 2024-01-01 |
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| series | Sensors |
| spelling | doaj.art-f642874a5f234acbab9f4ac6597d94d22024-01-10T15:09:18ZengMDPI AGSensors1424-82202024-01-0124126210.3390/s24010262Improvement in Multi-Angle Plane Wave Image Quality Using Minimum Variance Beamforming with Adaptive Signal CoherenceChe-Chou Shen0Chun-Lin Huang1Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei 106335, TaiwanDepartment of Electrical Engineering, National Taiwan University of Science and Technology, Taipei 106335, TaiwanFor ultrasound multi-angle plane wave (PW) imaging, the coherent PW compounding (CPWC) method provides limited image quality because of its conventional delay-and-sum beamforming. The delay-multiply-and-sum (DMAS) method is a coherence-based algorithm that improves image quality by introducing signal coherence among either receiving channels or PW transmit angles into the image output. The degree of signal coherence in DMAS is conventionally a global value for the entire image and thus the image resolution and contrast in the target region improves at the cost of speckle quality in the background region. In this study, the adaptive DMAS (ADMAS) is proposed such that the degree of signal coherence relies on the local characteristics of the image region to maintain the background speckle quality and the corresponding contrast-to-noise ratio (CNR). Subsequently, the ADMAS algorithm is further combined with minimum variance (MV) beamforming to increase the image resolution. The optimal MV estimation is determined to be in the direction of the PW transmit angle (Tx) for multi-angle PW imaging. Our results show that, using the PICMUS dataset, TxMV-ADMAS beamforming significantly improves the image quality compared with CPWC. When the <i>p</i> value is globally fixed to 2 as in conventional DMAS, though the main-lobe width and the image contrast in the experiments improve from 0.57 mm and 27.0 dB in CPWC, respectively, to 0.24 mm and 38.0 dB, the corresponding CNR decreases from 12.8 to 11.3 due to the degraded speckle quality. With the proposed ADMAS algorithm, however, the adaptive <i>p</i> value in DMAS beamforming helps to restore the CNR value to the same level of CPWC while the improvement in image resolution and contrast remains evident.https://www.mdpi.com/1424-8220/24/1/262plane wave imagingsignal coherencedelay-multiply-and-summinimum varianceadaptive delay-multiply-and-sum |
| spellingShingle | Che-Chou Shen Chun-Lin Huang Improvement in Multi-Angle Plane Wave Image Quality Using Minimum Variance Beamforming with Adaptive Signal Coherence Sensors plane wave imaging signal coherence delay-multiply-and-sum minimum variance adaptive delay-multiply-and-sum |
| title | Improvement in Multi-Angle Plane Wave Image Quality Using Minimum Variance Beamforming with Adaptive Signal Coherence |
| title_full | Improvement in Multi-Angle Plane Wave Image Quality Using Minimum Variance Beamforming with Adaptive Signal Coherence |
| title_fullStr | Improvement in Multi-Angle Plane Wave Image Quality Using Minimum Variance Beamforming with Adaptive Signal Coherence |
| title_full_unstemmed | Improvement in Multi-Angle Plane Wave Image Quality Using Minimum Variance Beamforming with Adaptive Signal Coherence |
| title_short | Improvement in Multi-Angle Plane Wave Image Quality Using Minimum Variance Beamforming with Adaptive Signal Coherence |
| title_sort | improvement in multi angle plane wave image quality using minimum variance beamforming with adaptive signal coherence |
| topic | plane wave imaging signal coherence delay-multiply-and-sum minimum variance adaptive delay-multiply-and-sum |
| url | https://www.mdpi.com/1424-8220/24/1/262 |
| work_keys_str_mv | AT chechoushen improvementinmultiangleplanewaveimagequalityusingminimumvariancebeamformingwithadaptivesignalcoherence AT chunlinhuang improvementinmultiangleplanewaveimagequalityusingminimumvariancebeamformingwithadaptivesignalcoherence |