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3-D freehand echocardiography for automatic left ventricle reconstruction and analysis based on multiple acoustic windows
A new method is proposed to reconstruct and analyze the left ventricle (LV) from multiple acoustic window three-dimensional (3-D) ultrasound acquired using a transthoracic 3-D rotational probe. Prior research in this area has been based on one acoustic window acquisition. However, the data suffers f...
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Published in: | IEEE transactions on medical imaging 2002-09, Vol.21 (9), p.1051-1058 |
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description | A new method is proposed to reconstruct and analyze the left ventricle (LV) from multiple acoustic window three-dimensional (3-D) ultrasound acquired using a transthoracic 3-D rotational probe. Prior research in this area has been based on one acoustic window acquisition. However, the data suffers from several limitations that degrade the reconstruction and reduce the clinical value of interpretation, such as the presence of shadow due to bone (ribs) and air (in the lungs) and motion of the probe during the acquisition. In this paper, we show how to overcome these limitations by automatically fusing information from multiple acoustic window sparse-view acquisitions and using a position sensor to track the probe in real time. Geometric constraints of the object shape, and spatiotemporal information relating to the image acquisition process, are used in new algorithms for 1) grouping endocardial edge cues from an initial image segmentation and 2) defining a novel reconstruction method that utilizes information from multiple acoustic windows. The new method has been validated on a phantom and three real heart data sets. In the phantom study, one finger of a latex glove was scanned from two acoustic windows and reconstructed using the new method. The volume error was measured to be less than 4%. In the clinical case study, 3-D ultrasound and magnetic resonance imaging (MRI) scanning were performed on the same healthy volunteers. Quantitative ejection fractions (EFs) and volume-time curves over a cardiac cycle were estimated using the new method and compared to cardiac MRI measurements. This showed that the new method agrees better with MRI measurements than the previous approach we have developed based on a single acoustic window. The EF errors of the new method with respect to MRI measurements were less than 6%. A more extensive clinical validation is required to establish whether these promising first results translate to a method suitable for routine clinical use. |
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Prior research in this area has been based on one acoustic window acquisition. However, the data suffers from several limitations that degrade the reconstruction and reduce the clinical value of interpretation, such as the presence of shadow due to bone (ribs) and air (in the lungs) and motion of the probe during the acquisition. In this paper, we show how to overcome these limitations by automatically fusing information from multiple acoustic window sparse-view acquisitions and using a position sensor to track the probe in real time. Geometric constraints of the object shape, and spatiotemporal information relating to the image acquisition process, are used in new algorithms for 1) grouping endocardial edge cues from an initial image segmentation and 2) defining a novel reconstruction method that utilizes information from multiple acoustic windows. The new method has been validated on a phantom and three real heart data sets. In the phantom study, one finger of a latex glove was scanned from two acoustic windows and reconstructed using the new method. The volume error was measured to be less than 4%. In the clinical case study, 3-D ultrasound and magnetic resonance imaging (MRI) scanning were performed on the same healthy volunteers. Quantitative ejection fractions (EFs) and volume-time curves over a cardiac cycle were estimated using the new method and compared to cardiac MRI measurements. This showed that the new method agrees better with MRI measurements than the previous approach we have developed based on a single acoustic window. The EF errors of the new method with respect to MRI measurements were less than 6%. 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Prior research in this area has been based on one acoustic window acquisition. However, the data suffers from several limitations that degrade the reconstruction and reduce the clinical value of interpretation, such as the presence of shadow due to bone (ribs) and air (in the lungs) and motion of the probe during the acquisition. In this paper, we show how to overcome these limitations by automatically fusing information from multiple acoustic window sparse-view acquisitions and using a position sensor to track the probe in real time. Geometric constraints of the object shape, and spatiotemporal information relating to the image acquisition process, are used in new algorithms for 1) grouping endocardial edge cues from an initial image segmentation and 2) defining a novel reconstruction method that utilizes information from multiple acoustic windows. The new method has been validated on a phantom and three real heart data sets. In the phantom study, one finger of a latex glove was scanned from two acoustic windows and reconstructed using the new method. The volume error was measured to be less than 4%. In the clinical case study, 3-D ultrasound and magnetic resonance imaging (MRI) scanning were performed on the same healthy volunteers. Quantitative ejection fractions (EFs) and volume-time curves over a cardiac cycle were estimated using the new method and compared to cardiac MRI measurements. This showed that the new method agrees better with MRI measurements than the previous approach we have developed based on a single acoustic window. The EF errors of the new method with respect to MRI measurements were less than 6%. A more extensive clinical validation is required to establish whether these promising first results translate to a method suitable for routine clinical use.</description><subject>Acoustic measurements</subject><subject>Acoustics</subject><subject>Acquisitions</subject><subject>Algorithms</subject><subject>Biological and medical sciences</subject><subject>Degradation</subject><subject>Echocardiography</subject><subject>Echocardiography, Three-Dimensional</subject><subject>Error analysis</subject><subject>Errors</subject><subject>Humans</subject><subject>Image Processing, Computer-Assisted</subject><subject>Image reconstruction</subject><subject>Imaging phantoms</subject><subject>Magnetic Resonance Imaging</subject><subject>Marketing</subject><subject>Medical sciences</subject><subject>Phantoms, Imaging</subject><subject>Probes</subject><subject>Reconstruction</subject><subject>Studies</subject><subject>Ultrasonic imaging</subject><subject>Ultrasonic variables measurement</subject><subject>Ultrasound</subject><subject>Ventricular Function, Left - physiology</subject><subject>Volume measurement</subject><issn>0278-0062</issn><issn>1558-254X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2002</creationdate><recordtype>article</recordtype><recordid>eNqF0s2L1DAYBvAgijuOnj0IEgQ_Lp3Nd9Kj7K66sOJlBW8lTd84WdpmNmld5r83ZQYGPKynQPPrw0N4EHpNyYZSUp_ffr_eMELYxhAhuHqCVlRKUzEpfj1FK8K0qQhR7Ay9yPmOECokqZ-jM8qkEkbzFdrz6hL7BLC1Y4fBbaOzqQvxd7K77R77mLCdpzjYKTjcg5_wHxinFFwPOIGLY57S7KYQR7wE2NH2-xwybm2GDpevw9xPYVe0dXHOS8pDGLv4kF-iZ972GV4dzzX6-eXq9uJbdfPj6_XF55vKSc6mSvKagqOtE9Z2rPXWUW4pADfOKaJ9KzSXLVOdooxJpjzhnlNfF2O47Bhfo4-H3F2K9zPkqRlCdtD3doTSqDHGkLomtSnyw6NSMyOY1OS_kBlaS1KKrdGnRyFVmgouqOGFvvuH3sU5ledcGgqhhSZLw_MDcinmnMA3uxQGm_YNJc0yiKYMolkG0RwGUf54e4yd2wG6kz8uoID3R2Czs71PdnQhn5wQShNaF_fm4AIAnK6pUooL_hfslMcn</recordid><startdate>20020901</startdate><enddate>20020901</enddate><creator>Xujiong Ye</creator><creator>Noble, J.A.</creator><creator>Atkinson, D.</creator><general>IEEE</general><general>Institute of Electrical and Electronics Engineers</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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Prior research in this area has been based on one acoustic window acquisition. However, the data suffers from several limitations that degrade the reconstruction and reduce the clinical value of interpretation, such as the presence of shadow due to bone (ribs) and air (in the lungs) and motion of the probe during the acquisition. In this paper, we show how to overcome these limitations by automatically fusing information from multiple acoustic window sparse-view acquisitions and using a position sensor to track the probe in real time. Geometric constraints of the object shape, and spatiotemporal information relating to the image acquisition process, are used in new algorithms for 1) grouping endocardial edge cues from an initial image segmentation and 2) defining a novel reconstruction method that utilizes information from multiple acoustic windows. The new method has been validated on a phantom and three real heart data sets. In the phantom study, one finger of a latex glove was scanned from two acoustic windows and reconstructed using the new method. The volume error was measured to be less than 4%. In the clinical case study, 3-D ultrasound and magnetic resonance imaging (MRI) scanning were performed on the same healthy volunteers. Quantitative ejection fractions (EFs) and volume-time curves over a cardiac cycle were estimated using the new method and compared to cardiac MRI measurements. This showed that the new method agrees better with MRI measurements than the previous approach we have developed based on a single acoustic window. The EF errors of the new method with respect to MRI measurements were less than 6%. A more extensive clinical validation is required to establish whether these promising first results translate to a method suitable for routine clinical use.</abstract><cop>New York, NY</cop><pub>IEEE</pub><pmid>12564873</pmid><doi>10.1109/TMI.2002.804436</doi><tpages>8</tpages></addata></record> |
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subjects | Acoustic measurements Acoustics Acquisitions Algorithms Biological and medical sciences Degradation Echocardiography Echocardiography, Three-Dimensional Error analysis Errors Humans Image Processing, Computer-Assisted Image reconstruction Imaging phantoms Magnetic Resonance Imaging Marketing Medical sciences Phantoms, Imaging Probes Reconstruction Studies Ultrasonic imaging Ultrasonic variables measurement Ultrasound Ventricular Function, Left - physiology Volume measurement |
title | 3-D freehand echocardiography for automatic left ventricle reconstruction and analysis based on multiple acoustic windows |
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