A. Danudibroto, J. Bersvendsen, O. Mirea, O. Gérard, J. D’hooge, E. Samset
Temporal alignment of echocardiographic sequences enables fair comparisons of multiple cardiac sequences by showing corresponding frames at given time points in the cardiac cycle. It is also essential for spatial registration of echo volumes where several acquisitions are combined for enhancement of image quality or forming larger field of view. In this study, three different image-based temporal alignment methods were investigated. First, a method based on dynamic time warping (DTW). Second, a spline-based method that optimized the similarity between temporal characteristic curves of the cardiac cycle using 1D cubic B-spline interpolation. Third, a method based on the spline-based method with piecewise modification. These methods were tested on in-vivo data sets of 19 echo sequences. For each sequence, the mitral valve opening (MVO) time was manually annotated. The results showed that the average MVO timing error for all methods are well under the time resolution of the sequences.
{"title":"Image-based temporal alignment of echocardiographic sequences","authors":"A. Danudibroto, J. Bersvendsen, O. Mirea, O. Gérard, J. D’hooge, E. Samset","doi":"10.1117/12.2216192","DOIUrl":"https://doi.org/10.1117/12.2216192","url":null,"abstract":"Temporal alignment of echocardiographic sequences enables fair comparisons of multiple cardiac sequences by showing corresponding frames at given time points in the cardiac cycle. It is also essential for spatial registration of echo volumes where several acquisitions are combined for enhancement of image quality or forming larger field of view. In this study, three different image-based temporal alignment methods were investigated. First, a method based on dynamic time warping (DTW). Second, a spline-based method that optimized the similarity between temporal characteristic curves of the cardiac cycle using 1D cubic B-spline interpolation. Third, a method based on the spline-based method with piecewise modification. These methods were tested on in-vivo data sets of 19 echo sequences. For each sequence, the mitral valve opening (MVO) time was manually annotated. The results showed that the average MVO timing error for all methods are well under the time resolution of the sequences.","PeriodicalId":228011,"journal":{"name":"SPIE Medical Imaging","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126757165","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Chunyu Li, Jiali Yang, Xu Li, Xiaoli Zhong, J. Song, Mingyue Ding, M. Yuchi
This paper presents a work of real-time 3-D image reconstruction for a 7.5-MHz, 24×24 row-column addressing array transducer. The transducer works with a predesigned transmit/receive module. After the raw data are captured by the NI PXIe data acquisition (DAQ) module, the following processing procedures are performed: delay and sum (DAS), base-line calibration, envelope detection, logarithm compression, down-sampling, gray scale mapping and 3-D display. These procedures are optimized for obtaining real-time 3-D images. Fixed-point focusing scheme is applied in delay and sum (DAS) to obtain line data from channel data. Zero-phase high-pass filter is used to calibrate the base-line shift of echo. The classical Hilbert transformation is adopted to detect the envelopes of echo. Logarithm compression is implemented to enlarge the weak signals and narrow the gap from the strong ones. Down-sampling reduces the amount of data to improve the processing speed. Linear gray scale mapping is introduced that the weakest signal is mapped to 0 and the strongest signal 255. The real-time 3-D images are displayed with multi-planar mode, which shows three orthogonal sections (vertical section, coronal section, transverse section). A trigger signal is sent from the transmit/receive module to the DAQ module at the start of each volume data generation to ensure synchronization between these two modules. All procedures, include data acquisition (DAQ), signal processing and image display, are programmed on the platform of LabVIEW. 675MB raw echo data are acquired in one minute to generate 24×24×48, 27fps 3-D images. The experiment on the strong reflection object (aluminum slice) shows the feasibility of the whole process from raw data to real-time 3-D images.
{"title":"Real-time 3D image reconstruction of a 24×24 row-column addressing array: from raw data to image","authors":"Chunyu Li, Jiali Yang, Xu Li, Xiaoli Zhong, J. Song, Mingyue Ding, M. Yuchi","doi":"10.1117/12.2216069","DOIUrl":"https://doi.org/10.1117/12.2216069","url":null,"abstract":"This paper presents a work of real-time 3-D image reconstruction for a 7.5-MHz, 24×24 row-column addressing array transducer. The transducer works with a predesigned transmit/receive module. After the raw data are captured by the NI PXIe data acquisition (DAQ) module, the following processing procedures are performed: delay and sum (DAS), base-line calibration, envelope detection, logarithm compression, down-sampling, gray scale mapping and 3-D display. These procedures are optimized for obtaining real-time 3-D images. Fixed-point focusing scheme is applied in delay and sum (DAS) to obtain line data from channel data. Zero-phase high-pass filter is used to calibrate the base-line shift of echo. The classical Hilbert transformation is adopted to detect the envelopes of echo. Logarithm compression is implemented to enlarge the weak signals and narrow the gap from the strong ones. Down-sampling reduces the amount of data to improve the processing speed. Linear gray scale mapping is introduced that the weakest signal is mapped to 0 and the strongest signal 255. The real-time 3-D images are displayed with multi-planar mode, which shows three orthogonal sections (vertical section, coronal section, transverse section). A trigger signal is sent from the transmit/receive module to the DAQ module at the start of each volume data generation to ensure synchronization between these two modules. All procedures, include data acquisition (DAQ), signal processing and image display, are programmed on the platform of LabVIEW. 675MB raw echo data are acquired in one minute to generate 24×24×48, 27fps 3-D images. The experiment on the strong reflection object (aluminum slice) shows the feasibility of the whole process from raw data to real-time 3-D images.","PeriodicalId":228011,"journal":{"name":"SPIE Medical Imaging","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127525212","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
H. Bouzari, Mathias Engholm, T. Christiansen, C. Beers, A. Lei, M. Stuart, S. Nikolov, E. Thomsen, J. Jensen
The synthetic aperture (SA) technique can be used for achieving real-time volumetric ultrasound imaging using 2-D row-column addressed transducers. This paper investigates SA volumetric imaging performance of an in-house prototyped 3 MHz λ/2-pitch 62+62 element piezoelectric 2-D row-column addressed transducer array. Utilizing single element transmit events, a volume rate of 90 Hz down to 14 cm deep is achieved. Data are obtained using the experimental ultrasound scanner SARUS with a 70 MHz sampling frequency and beamformed using a delay-and-sum (DAS) approach. A signal-to-noise ratio of up to 32 dB is measured on the beamformed images of a tissue mimicking phantom with attenuation of 0.5 dB cm-1 MHz-1, from the surface of the probe to the penetration depth of 300λ. Measured lateral resolution as Full-Width-at-Half-Maximum (FWHM) is between 4λ and 10λ for 18% to 65% of the penetration depth from the surface of the probe. The averaged contrast is 13 dB for the same range. The imaging performance assessment results may represent a reference guide for possible applications of such an array in different medical fields.
合成孔径(SA)技术可用于实现实时体积超声成像使用二维行列寻址换能器。本文研究了一种自制的3mhz λ/2-螺距62+62单元压电二维行列寻址传感器阵列的SA体积成像性能。利用单元件传输事件，可以实现90 Hz的体积速率，深度可达14厘米。数据使用实验超声扫描仪SARUS获得，采样频率为70 MHz，波束形成采用延迟和(DAS)方法。在从探头表面到穿透深度为300λ的衰减为0.5 dB cm-1 MHz-1的组织模拟幻影的波束形成图像上测量了高达32 dB的信噪比。测量的横向分辨率为半最大全宽度(FWHM)，在距离探头表面18%至65%的穿透深度范围内，分辨率在4λ至10λ之间。在相同的范围内，平均对比度为13 dB。成像性能评估结果可为该阵列在不同医学领域的可能应用提供参考指南。
{"title":"Volumetric synthetic aperture imaging with a piezoelectric 2D row-column probe","authors":"H. Bouzari, Mathias Engholm, T. Christiansen, C. Beers, A. Lei, M. Stuart, S. Nikolov, E. Thomsen, J. Jensen","doi":"10.1117/12.2216074","DOIUrl":"https://doi.org/10.1117/12.2216074","url":null,"abstract":"The synthetic aperture (SA) technique can be used for achieving real-time volumetric ultrasound imaging using 2-D row-column addressed transducers. This paper investigates SA volumetric imaging performance of an in-house prototyped 3 MHz λ/2-pitch 62+62 element piezoelectric 2-D row-column addressed transducer array. Utilizing single element transmit events, a volume rate of 90 Hz down to 14 cm deep is achieved. Data are obtained using the experimental ultrasound scanner SARUS with a 70 MHz sampling frequency and beamformed using a delay-and-sum (DAS) approach. A signal-to-noise ratio of up to 32 dB is measured on the beamformed images of a tissue mimicking phantom with attenuation of 0.5 dB cm-1 MHz-1, from the surface of the probe to the penetration depth of 300λ. Measured lateral resolution as Full-Width-at-Half-Maximum (FWHM) is between 4λ and 10λ for 18% to 65% of the penetration depth from the surface of the probe. The averaged contrast is 13 dB for the same range. The imaging performance assessment results may represent a reference guide for possible applications of such an array in different medical fields.","PeriodicalId":228011,"journal":{"name":"SPIE Medical Imaging","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124199117","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Tao Li, Pei Zhou, Mingyue Ding, Yongwei Mi, Yiyong Li, Ji Zhang
The aim of this study was to evaluate the diagnostic performance of virtual touch tissue imaging (VTI) based on ARFI elastography technique for differentiating malignant from benign thyroid nodules. One hundred pathologically proven thyroid nodules (80 benign, 20 malignant) in 76 participants were recruited in this study. The likelihood of malignancy in the light of VTI features was scored into 6 levels by one experienced sonogist who was blinded to pathological results. In addition, the mean gray value within the thyroid nodule (mGVTN) derived from VTI image was calculated for quantitative analysis. Receiver-operating characteristic curve (ROC) analyses were performed to assess the diagnostic performance of VTI score and mGVTN. The frequency of malignant nodules (11/20) classified between VTI levels 4 to 6 was more than that of benign nodules (6/80) (p <0.001). The mGVTN of malignant nodules (45±23) was significantly lower than that of benign nodules (115±58) (p <0.001), where the range of mGVTN was from 0 to 255. The sensitivity, specificity, accuracy, positive predictive value and negative predictive value of VTI score were 55.0%, 92.5%, 85.0%, 64.7% and 89.2%, respectively. For mGVTN, those values were 70.0%, 90.0%, 86.0%, 63.6% and 92.3%, respectively. In conclusion, the VTI image seemed to be an effective tool in the differential diagnosis of thyroid nodules. The diagnosis performance of mGVTN was almost consistent with that of VTI score, which indicated that the mGVTN as a quantitative parameter might facilitate doctors diagnosing malignant thyroid nodules by VTI.
{"title":"Differential diagnosis of thyroid nodules with virtual touch tissue imaging of ARFI elastography","authors":"Tao Li, Pei Zhou, Mingyue Ding, Yongwei Mi, Yiyong Li, Ji Zhang","doi":"10.1117/12.2216190","DOIUrl":"https://doi.org/10.1117/12.2216190","url":null,"abstract":"The aim of this study was to evaluate the diagnostic performance of virtual touch tissue imaging (VTI) based on ARFI elastography technique for differentiating malignant from benign thyroid nodules. One hundred pathologically proven thyroid nodules (80 benign, 20 malignant) in 76 participants were recruited in this study. The likelihood of malignancy in the light of VTI features was scored into 6 levels by one experienced sonogist who was blinded to pathological results. In addition, the mean gray value within the thyroid nodule (mGVTN) derived from VTI image was calculated for quantitative analysis. Receiver-operating characteristic curve (ROC) analyses were performed to assess the diagnostic performance of VTI score and mGVTN. The frequency of malignant nodules (11/20) classified between VTI levels 4 to 6 was more than that of benign nodules (6/80) (p <0.001). The mGVTN of malignant nodules (45±23) was significantly lower than that of benign nodules (115±58) (p <0.001), where the range of mGVTN was from 0 to 255. The sensitivity, specificity, accuracy, positive predictive value and negative predictive value of VTI score were 55.0%, 92.5%, 85.0%, 64.7% and 89.2%, respectively. For mGVTN, those values were 70.0%, 90.0%, 86.0%, 63.6% and 92.3%, respectively. In conclusion, the VTI image seemed to be an effective tool in the differential diagnosis of thyroid nodules. The diagnosis performance of mGVTN was almost consistent with that of VTI score, which indicated that the mGVTN as a quantitative parameter might facilitate doctors diagnosing malignant thyroid nodules by VTI.","PeriodicalId":228011,"journal":{"name":"SPIE Medical Imaging","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114356056","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Conventional ultrasonography reconstruction techniques, such as B-mode, are based on a simple wave propagation model derived from a high frequency approximation. Therefore, to minimize model mismatch, the central frequency of the input pulse is typically chosen between 3 and 15 megahertz. Despite the increase in theoretical resolution, operating at higher frequencies comes at the cost of lower signal-to-noise ratio. This ultimately degrades the image contrast and overall quality at higher imaging depths. To address this issue, we investigate a reflection imaging technique, known as reverse time migration, which uses a more accurate propagation model for reconstruction. We present preliminary simulation results as well as physical phantom image reconstructions obtained using data acquired with a breast imaging ultrasound tomography prototype. The original reconstructions are filtered to remove low-wavenumber artifacts that arise due to the inclusion of the direct arrivals. We demonstrate the advantage of using an accurate sound speed model in the reverse time migration process. We also explain how the increase in computational complexity can be mitigated using a frequency domain approach and a parallel computing platform.
{"title":"Ultrasound breast imaging using frequency domain reverse time migration","authors":"O. Roy, M. Zuberi, R. Pratt, N. Duric","doi":"10.1117/12.2218366","DOIUrl":"https://doi.org/10.1117/12.2218366","url":null,"abstract":"Conventional ultrasonography reconstruction techniques, such as B-mode, are based on a simple wave propagation model derived from a high frequency approximation. Therefore, to minimize model mismatch, the central frequency of the input pulse is typically chosen between 3 and 15 megahertz. Despite the increase in theoretical resolution, operating at higher frequencies comes at the cost of lower signal-to-noise ratio. This ultimately degrades the image contrast and overall quality at higher imaging depths. To address this issue, we investigate a reflection imaging technique, known as reverse time migration, which uses a more accurate propagation model for reconstruction. We present preliminary simulation results as well as physical phantom image reconstructions obtained using data acquired with a breast imaging ultrasound tomography prototype. The original reconstructions are filtered to remove low-wavenumber artifacts that arise due to the inclusion of the direct arrivals. We demonstrate the advantage of using an accurate sound speed model in the reverse time migration process. We also explain how the increase in computational complexity can be mitigated using a frequency domain approach and a parallel computing platform.","PeriodicalId":228011,"journal":{"name":"SPIE Medical Imaging","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121864799","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
J. Kishimoto, A. Fenster, F. Salehi, W. Romano, David S. C. Lee, S. de Ribaupierre
Dilation of the cerebral ventricles is a common condition in preterm neonates with intraventricular hemorrhage (IVH). This post hemorrhagic ventricle dilation (PHVD) can lead to lifelong neurological impairment through ischemic injury due to increased intracranial pressure and without treatment, can lead to death. Clinically, 2D ultrasound (US) through the fontanelles ('soft spots') of the patients are serially acquired to monitor the progression of the ventricle dilation. These images are used to determine when interventional therapies such as needle aspiration of the built up cerebrospinal fluid (CSF) ('ventricle tap', VT) might be indicated for a patient; however, quantitative measurements of the growth of the ventricles are often not performed. There is no consensus on when a neonate with PHVD should have an intervention and often interventions are performed after the potential for brain damage is quite high. Previously we have developed and validated a 3D US system to monitor the progression of ventricle volumes (VV) in IVH patients. We will describe the potential utility of quantitative 2D and 3D US to monitor and manage PHVD in neonates. Specifically, we will look to determine image-based measurement thresholds for patients who will require VT in comparison to patients with PHVD who resolve without intervention. Additionally, since many patients who have an initial VT will require subsequent interventions, we look at the potential for US to determine which PHVD patients will require additional VT after the initial one has been performed.
{"title":"Quantitative head ultrasound measurements to determine thresholds for preterm neonates requiring interventional therapies following intraventricular hemorrhage","authors":"J. Kishimoto, A. Fenster, F. Salehi, W. Romano, David S. C. Lee, S. de Ribaupierre","doi":"10.1117/12.2216870","DOIUrl":"https://doi.org/10.1117/12.2216870","url":null,"abstract":"Dilation of the cerebral ventricles is a common condition in preterm neonates with intraventricular hemorrhage (IVH). This post hemorrhagic ventricle dilation (PHVD) can lead to lifelong neurological impairment through ischemic injury due to increased intracranial pressure and without treatment, can lead to death. Clinically, 2D ultrasound (US) through the fontanelles ('soft spots') of the patients are serially acquired to monitor the progression of the ventricle dilation. These images are used to determine when interventional therapies such as needle aspiration of the built up cerebrospinal fluid (CSF) ('ventricle tap', VT) might be indicated for a patient; however, quantitative measurements of the growth of the ventricles are often not performed. There is no consensus on when a neonate with PHVD should have an intervention and often interventions are performed after the potential for brain damage is quite high. Previously we have developed and validated a 3D US system to monitor the progression of ventricle volumes (VV) in IVH patients. We will describe the potential utility of quantitative 2D and 3D US to monitor and manage PHVD in neonates. Specifically, we will look to determine image-based measurement thresholds for patients who will require VT in comparison to patients with PHVD who resolve without intervention. Additionally, since many patients who have an initial VT will require subsequent interventions, we look at the potential for US to determine which PHVD patients will require additional VT after the initial one has been performed.","PeriodicalId":228011,"journal":{"name":"SPIE Medical Imaging","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122502327","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Spectral CT using a photon-counting x-ray detector (PCXD) can potentially increase accuracy of measuring tissue composition. However, PCXD spectral measurements suffer from distortion due to charge sharing, pulse pileup, and Kescape energy loss. This study proposes two novel artificial neural network (ANN)-based algorithms: one to model and compensate for the distortion, and another one to directly correct for the distortion. The ANN-based distortion model was obtained by training to learn the distortion from a set of projections with a calibration scan. The ANN distortion was then applied in the forward statistical model to compensate for distortion in the projection decomposition. ANN was also used to learn to correct distortions directly in projections. The resulting corrected projections were used for reconstructing the image, denoising via joint bilateral filtration, and decomposition into three-material basis functions: Compton scattering, the photoelectric effect, and iodine. The ANN-based distortion model proved to be more robust to noise and worked better compared to using an imperfect parametric distortion model. In the presence of noise, the mean relative errors in iodine concentration estimation were 11.82% (ANN distortion model) and 16.72% (parametric model). With distortion correction, the mean relative error in iodine concentration estimation was improved by 50% over direct decomposition from distorted data. With our joint bilateral filtration, the resulting material image quality and iodine detectability as defined by the contrast-to-noise ratio were greatly enhanced allowing iodine concentrations as low as 2 mg/ml to be detected. Future work will be dedicated to experimental evaluation of our ANN-based methods using 3D-printed phantoms.
{"title":"Novel approaches to address spectral distortions in photon counting x-ray CT using artificial neural networks","authors":"M. Touch, D. Clark, W. Barber, C. Badea","doi":"10.1117/12.2217037","DOIUrl":"https://doi.org/10.1117/12.2217037","url":null,"abstract":"Spectral CT using a photon-counting x-ray detector (PCXD) can potentially increase accuracy of measuring tissue composition. However, PCXD spectral measurements suffer from distortion due to charge sharing, pulse pileup, and Kescape energy loss. This study proposes two novel artificial neural network (ANN)-based algorithms: one to model and compensate for the distortion, and another one to directly correct for the distortion. The ANN-based distortion model was obtained by training to learn the distortion from a set of projections with a calibration scan. The ANN distortion was then applied in the forward statistical model to compensate for distortion in the projection decomposition. ANN was also used to learn to correct distortions directly in projections. The resulting corrected projections were used for reconstructing the image, denoising via joint bilateral filtration, and decomposition into three-material basis functions: Compton scattering, the photoelectric effect, and iodine. The ANN-based distortion model proved to be more robust to noise and worked better compared to using an imperfect parametric distortion model. In the presence of noise, the mean relative errors in iodine concentration estimation were 11.82% (ANN distortion model) and 16.72% (parametric model). With distortion correction, the mean relative error in iodine concentration estimation was improved by 50% over direct decomposition from distorted data. With our joint bilateral filtration, the resulting material image quality and iodine detectability as defined by the contrast-to-noise ratio were greatly enhanced allowing iodine concentrations as low as 2 mg/ml to be detected. Future work will be dedicated to experimental evaluation of our ANN-based methods using 3D-printed phantoms.","PeriodicalId":228011,"journal":{"name":"SPIE Medical Imaging","volume":"9 12","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131438230","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hiroki Murakami, Tsuneo Watanabe, D. Fukuoka, N. Terabayashi, T. Hara, C. Muramatsu, H. Fujita
The word "Locomotive syndrome" has been proposed to describe the state of requiring care by musculoskeletal disorders and its high-risk condition. Reduction of the knee extension strength is cited as one of the risk factors, and the accurate measurement of the strength is needed for the evaluation. The measurement of knee extension strength using a dynamometer is one of the most direct and quantitative methods. This study aims to develop a system for measuring the knee extension strength using the ultrasound images of the rectus femoris muscles obtained with non-invasive ultrasonic diagnostic equipment. First, we extract the muscle area from the ultrasound images and determine the image features, such as the thickness of the muscle. We combine these features and physical features, such as the patient’s height, and build a regression model of the knee extension strength from training data. We have developed a system for estimating the knee extension strength by applying the regression model to the features obtained from test data. Using the test data of 168 cases, correlation coefficient value between the measured values and estimated values was 0.82. This result suggests that this system can estimate knee extension strength with high accuracy.
{"title":"Development of estimation system of knee extension strength using image features in ultrasound images of rectus femoris","authors":"Hiroki Murakami, Tsuneo Watanabe, D. Fukuoka, N. Terabayashi, T. Hara, C. Muramatsu, H. Fujita","doi":"10.1117/12.2214843","DOIUrl":"https://doi.org/10.1117/12.2214843","url":null,"abstract":"The word \"Locomotive syndrome\" has been proposed to describe the state of requiring care by musculoskeletal disorders and its high-risk condition. Reduction of the knee extension strength is cited as one of the risk factors, and the accurate measurement of the strength is needed for the evaluation. The measurement of knee extension strength using a dynamometer is one of the most direct and quantitative methods. This study aims to develop a system for measuring the knee extension strength using the ultrasound images of the rectus femoris muscles obtained with non-invasive ultrasonic diagnostic equipment. First, we extract the muscle area from the ultrasound images and determine the image features, such as the thickness of the muscle. We combine these features and physical features, such as the patient’s height, and build a regression model of the knee extension strength from training data. We have developed a system for estimating the knee extension strength by applying the regression model to the features obtained from test data. Using the test data of 168 cases, correlation coefficient value between the measured values and estimated values was 0.82. This result suggests that this system can estimate knee extension strength with high accuracy.","PeriodicalId":228011,"journal":{"name":"SPIE Medical Imaging","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131598942","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Image reconstruction based on iterative minimization of a penalized weighted least-square criteria has become an important topic of research in X-ray computed tomography. This topic is motivated by increasing evidence that such a formalism may enable a significant reduction in dose imparted to the patient while maintaining or improving image quality. One important issue associated with this iterative image reconstruction concept is slow convergence and the associated computational effort. For this reason, there is interest in finding methods that produce approximate versions of the targeted image with a small number of iterations and an acceptable level of discrepancy. We introduce here a novel method to produce such approximations: ordered subsets in combination with iterative coordinate descent. Preliminary results demonstrate that this method can produce, within 10 iterations and using only a constant image as initial condition, satisfactory reconstructions that retain the noise properties of the targeted image.
{"title":"Iterative CT reconstruction using coordinate descent with ordered subsets of data","authors":"F. Noo, K. Hahn, H. Schöndube, K. Stierstorfer","doi":"10.1117/12.2217558","DOIUrl":"https://doi.org/10.1117/12.2217558","url":null,"abstract":"Image reconstruction based on iterative minimization of a penalized weighted least-square criteria has become an important topic of research in X-ray computed tomography. This topic is motivated by increasing evidence that such a formalism may enable a significant reduction in dose imparted to the patient while maintaining or improving image quality. One important issue associated with this iterative image reconstruction concept is slow convergence and the associated computational effort. For this reason, there is interest in finding methods that produce approximate versions of the targeted image with a small number of iterations and an acceptable level of discrepancy. We introduce here a novel method to produce such approximations: ordered subsets in combination with iterative coordinate descent. Preliminary results demonstrate that this method can produce, within 10 iterations and using only a constant image as initial condition, satisfactory reconstructions that retain the noise properties of the targeted image.","PeriodicalId":228011,"journal":{"name":"SPIE Medical Imaging","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123373075","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
High imaging dose has been a concern in computed tomography perfusion (CTP) as repeated scans are performed at the same location of a patient. On the other hand, signal changes only occur at limited regions in CT acquired at different time points. In this work, we propose a new reconstruction strategy by effectively utilizing the initial phase high-quality CT to reconstruct the later phase CT acquired with a low-dose protocol. In the proposed strategy, initial high-quality CT is considered as a base image and enhanced signal (ES) is reconstructed directly by minimizing the penalized weighted least-square (PWLS) criterion. The proposed PWLS-ES strategy converts the conventional CT reconstruction into a sparse signal reconstruction problem. Digital and anthropomorphic phantom studies were performed to evaluate the performance of the proposed PWLS-ES strategy. Both phantom studies show that the proposed PWLS-ES method outperforms the standard iterative CT reconstruction algorithm based on the same PWLS criterion according to various quantitative metrics including root mean squared error (RMSE) and the universal quality index (UQI).
{"title":"Direct reconstruction of enhanced signal in computed tomography perfusion","authors":"Bin Li, Qingwen Lyu, Jianhua Ma, Jing Wang","doi":"10.1117/12.2216998","DOIUrl":"https://doi.org/10.1117/12.2216998","url":null,"abstract":"High imaging dose has been a concern in computed tomography perfusion (CTP) as repeated scans are performed at the same location of a patient. On the other hand, signal changes only occur at limited regions in CT acquired at different time points. In this work, we propose a new reconstruction strategy by effectively utilizing the initial phase high-quality CT to reconstruct the later phase CT acquired with a low-dose protocol. In the proposed strategy, initial high-quality CT is considered as a base image and enhanced signal (ES) is reconstructed directly by minimizing the penalized weighted least-square (PWLS) criterion. The proposed PWLS-ES strategy converts the conventional CT reconstruction into a sparse signal reconstruction problem. Digital and anthropomorphic phantom studies were performed to evaluate the performance of the proposed PWLS-ES strategy. Both phantom studies show that the proposed PWLS-ES method outperforms the standard iterative CT reconstruction algorithm based on the same PWLS criterion according to various quantitative metrics including root mean squared error (RMSE) and the universal quality index (UQI).","PeriodicalId":228011,"journal":{"name":"SPIE Medical Imaging","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134450529","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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