Ramin Moshavegh, Jonas Jensen, C. A. Villagómez-Hoyos, M. Stuart, M. Hemmsen, J. Jensen
Synthetic Aperture (SA) imaging produces high-quality images and velocity estimates of both slow and fast flow at high frame rates. However, grating lobe artifacts can appear both in transmission and reception. These affect the image quality and the frame rate. Therefore optimization of parameters effecting the image quality of SA is of great importance, and this paper proposes an advanced procedure for optimizing the parameters essential for acquiring an optimal image quality, while generating high resolution SA images. Optimization of the image quality is mainly performed based on measures such as F-number, number of emissions and the aperture size. They are considered to be the most contributing acquisition factors in the quality of the high resolution images in SA. Therefore, the performance of image quality is quantified in terms of full-width at half maximum (FWHM) and the cystic resolution (CTR). The results of the study showed that SA imaging with only 32 emissions and maximum sweep angle of 22 degrees yields a very good image quality compared with using 256 emissions and the full aperture size. Therefore the number of emissions and the maximum sweep angle in the SA can be optimized to reach a reasonably good performance, and to increase the frame rate by lowering the required number of emissions. All the measurements are performed using the experimental SARUS scanner connected to a λ/2-pitch transducer. A wire phantom and a tissue mimicking phantom containing anechoic cysts are scanned using the optimized parameters for the transducer. Measurements coincide with simulations.
{"title":"Optimization of synthetic aperture image quality","authors":"Ramin Moshavegh, Jonas Jensen, C. A. Villagómez-Hoyos, M. Stuart, M. Hemmsen, J. Jensen","doi":"10.1117/12.2216506","DOIUrl":"https://doi.org/10.1117/12.2216506","url":null,"abstract":"Synthetic Aperture (SA) imaging produces high-quality images and velocity estimates of both slow and fast flow at high frame rates. However, grating lobe artifacts can appear both in transmission and reception. These affect the image quality and the frame rate. Therefore optimization of parameters effecting the image quality of SA is of great importance, and this paper proposes an advanced procedure for optimizing the parameters essential for acquiring an optimal image quality, while generating high resolution SA images. Optimization of the image quality is mainly performed based on measures such as F-number, number of emissions and the aperture size. They are considered to be the most contributing acquisition factors in the quality of the high resolution images in SA. Therefore, the performance of image quality is quantified in terms of full-width at half maximum (FWHM) and the cystic resolution (CTR). The results of the study showed that SA imaging with only 32 emissions and maximum sweep angle of 22 degrees yields a very good image quality compared with using 256 emissions and the full aperture size. Therefore the number of emissions and the maximum sweep angle in the SA can be optimized to reach a reasonably good performance, and to increase the frame rate by lowering the required number of emissions. All the measurements are performed using the experimental SARUS scanner connected to a λ/2-pitch transducer. A wire phantom and a tissue mimicking phantom containing anechoic cysts are scanned using the optimized parameters for the transducer. Measurements coincide with simulations.","PeriodicalId":228011,"journal":{"name":"SPIE Medical Imaging","volume":"44 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":"126099850","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}
M. Gangeh, A. Raheem, Hadi Tadayyon, Simon Liu, Farnoosh Hadizad, G. Czarnota
Breast cancer is one of the most common cancer types accounting for 29% of all cancer cases. Early detection and treatment has a crucial impact on improving the survival of affected patients. Ultrasound (US) is non-ionizing, portable, inexpensive, and real-time imaging modality for screening and quantifying breast cancer. Due to these attractive attributes, the last decade has witnessed many studies on using quantitative ultrasound (QUS) methods in tissue characterization. However, these studies have mainly been limited to 2-D QUS methods using hand-held US (HHUS) scanners. With the availability of automated breast ultrasound (ABUS) technology, this study is the first to develop 3-D QUS methods for the ABUS visualization of breast tumours. Using an ABUS system, unlike the manual 2-D HHUS device, the whole patient’s breast was scanned in an automated manner. The acquired frames were subsequently examined and a region of interest (ROI) was selected in each frame where tumour was identified. Standard 2-D QUS methods were used to compute spectral and backscatter coefficient (BSC) parametric maps on the selected ROIs. Next, the computed 2-D parameters were mapped to a Cartesian 3-D space, interpolated, and rendered to provide a transparent color-coded visualization of the entire breast tumour. Such 3-D visualization can potentially be used for further analysis of the breast tumours in terms of their size and extension. Moreover, the 3-D volumetric scans can be used for tissue characterization and the categorization of breast tumours as benign or malignant by quantifying the computed parametric maps over the whole tumour volume.
{"title":"Breast tumour visualization using 3D quantitative ultrasound methods","authors":"M. Gangeh, A. Raheem, Hadi Tadayyon, Simon Liu, Farnoosh Hadizad, G. Czarnota","doi":"10.1117/12.2213504","DOIUrl":"https://doi.org/10.1117/12.2213504","url":null,"abstract":"Breast cancer is one of the most common cancer types accounting for 29% of all cancer cases. Early detection and treatment has a crucial impact on improving the survival of affected patients. Ultrasound (US) is non-ionizing, portable, inexpensive, and real-time imaging modality for screening and quantifying breast cancer. Due to these attractive attributes, the last decade has witnessed many studies on using quantitative ultrasound (QUS) methods in tissue characterization. However, these studies have mainly been limited to 2-D QUS methods using hand-held US (HHUS) scanners. With the availability of automated breast ultrasound (ABUS) technology, this study is the first to develop 3-D QUS methods for the ABUS visualization of breast tumours. Using an ABUS system, unlike the manual 2-D HHUS device, the whole patient’s breast was scanned in an automated manner. The acquired frames were subsequently examined and a region of interest (ROI) was selected in each frame where tumour was identified. Standard 2-D QUS methods were used to compute spectral and backscatter coefficient (BSC) parametric maps on the selected ROIs. Next, the computed 2-D parameters were mapped to a Cartesian 3-D space, interpolated, and rendered to provide a transparent color-coded visualization of the entire breast tumour. Such 3-D visualization can potentially be used for further analysis of the breast tumours in terms of their size and extension. Moreover, the 3-D volumetric scans can be used for tissue characterization and the categorization of breast tumours as benign or malignant by quantifying the computed parametric maps over the whole tumour volume.","PeriodicalId":228011,"journal":{"name":"SPIE Medical Imaging","volume":"88 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":"123591850","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. Hariharan, Nima Aklaghi, C. Baker, H. Rangwala, J. Kosecka, S. Sikdar
In spite of major advances in biomechanical design of upper extremity prosthetics, these devices continue to lack intuitive control. Conventional myoelectric control strategies typically utilize electromyography (EMG) signal amplitude sensed from forearm muscles. EMG has limited specificity in resolving deep muscle activity and poor signal-to-noise ratio. We have been investigating alternative control strategies that rely on real-time ultrasound imaging that can overcome many of the limitations of EMG. In this work, we present an ultrasound image sequence classification method that utilizes spatiotemporal features to describe muscle activity and classify motor intent. Ultrasound images of the forearm muscles were obtained from able-bodied subjects and a trans-radial amputee while they attempted different hand movements. A grid-based approach is used to test the feasibility of using spatio-temporal features by classifying hand motions performed by the subjects. Using the leave-one-out cross validation on image sequences acquired from able-bodied subjects, we observe that the grid-based approach is able to discern four hand motions with 95.31% accuracy. In case of the trans-radial amputee, we are able to discern three hand motions with 80% accuracy. In a second set of experiments, we study classification accuracy by extracting spatio-temporal sub-sequences the depict activity due to the motion of local anatomical interfaces. Short time and space limited cuboidal sequences are initially extracted and assigned an optical flow behavior label, based on a response function. The image space is clustered based on the location of cuboids and features calculated from the cuboids in each cluster. Using sequences of known motions, we extract feature vectors that describe said motion. A K-nearest neighbor classifier is designed for classification experiments. Using the leave-one-out cross validation on image sequences for an amputee subject, we demonstrate that the classifier is able to discern three important hand motions with an accuracy of 93.33% accuracy, 91–100% precision and 80–100% recall rate. We anticipate that ultrasound imaging based methods will address some limitations of conventional myoelectric sensing, while adding advantages inherent to ultrasound imaging.
{"title":"Classification of motor intent in transradial amputees using sonomyography and spatio-temporal image analysis","authors":"H. Hariharan, Nima Aklaghi, C. Baker, H. Rangwala, J. Kosecka, S. Sikdar","doi":"10.1117/12.2217174","DOIUrl":"https://doi.org/10.1117/12.2217174","url":null,"abstract":"In spite of major advances in biomechanical design of upper extremity prosthetics, these devices continue to lack intuitive control. Conventional myoelectric control strategies typically utilize electromyography (EMG) signal amplitude sensed from forearm muscles. EMG has limited specificity in resolving deep muscle activity and poor signal-to-noise ratio. We have been investigating alternative control strategies that rely on real-time ultrasound imaging that can overcome many of the limitations of EMG. In this work, we present an ultrasound image sequence classification method that utilizes spatiotemporal features to describe muscle activity and classify motor intent. Ultrasound images of the forearm muscles were obtained from able-bodied subjects and a trans-radial amputee while they attempted different hand movements. A grid-based approach is used to test the feasibility of using spatio-temporal features by classifying hand motions performed by the subjects. Using the leave-one-out cross validation on image sequences acquired from able-bodied subjects, we observe that the grid-based approach is able to discern four hand motions with 95.31% accuracy. In case of the trans-radial amputee, we are able to discern three hand motions with 80% accuracy. In a second set of experiments, we study classification accuracy by extracting spatio-temporal sub-sequences the depict activity due to the motion of local anatomical interfaces. Short time and space limited cuboidal sequences are initially extracted and assigned an optical flow behavior label, based on a response function. The image space is clustered based on the location of cuboids and features calculated from the cuboids in each cluster. Using sequences of known motions, we extract feature vectors that describe said motion. A K-nearest neighbor classifier is designed for classification experiments. Using the leave-one-out cross validation on image sequences for an amputee subject, we demonstrate that the classifier is able to discern three important hand motions with an accuracy of 93.33% accuracy, 91–100% precision and 80–100% recall rate. We anticipate that ultrasound imaging based methods will address some limitations of conventional myoelectric sensing, while adding advantages inherent to ultrasound imaging.","PeriodicalId":228011,"journal":{"name":"SPIE Medical Imaging","volume":"36 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":"125336444","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}
Yuxin Wang, Peng Gu, Won-Mean Lee, M. Roubidoux, S. Du, J. Yuan, Xueding Wang, P. Carson
Segmentation of an ultrasound image into functional tissues is of great importance to clinical diagnosis of breast cancer. However, many studies are found to segment only the mass of interest and not all major tissues. Differences and inconsistencies in ultrasound interpretation call for an automated segmentation method to make results operator-independent. Furthermore, manual segmentation of entire three-dimensional (3D) ultrasound volumes is time-consuming, resource-intensive, and clinically impractical. Here, we propose an automated algorithm to segment 3D ultrasound volumes into three major tissue types: cyst/mass, fatty tissue, and fibro-glandular tissue. To test its efficacy and consistency, the proposed automated method was employed on a database of 21 cases of whole breast ultrasound. Experimental results show that our proposed method not only distinguishes fat and non-fat tissues correctly, but performs well in classifying cyst/mass. Comparison of density assessment between the automated method and manual segmentation demonstrates good consistency with an accuracy of 85.7%. Quantitative comparison of corresponding tissue volumes, which uses overlap ratio, gives an average similarity of 74.54%, consistent with values seen in MRI brain segmentations. Thus, our proposed method exhibits great potential as an automated approach to segment 3D whole breast ultrasound volumes into functionally distinct tissues that may help to correct ultrasound speed of sound aberrations and assist in density based prognosis of breast cancer.
{"title":"Automated 3D ultrasound image segmentation for assistant diagnosis of breast cancer","authors":"Yuxin Wang, Peng Gu, Won-Mean Lee, M. Roubidoux, S. Du, J. Yuan, Xueding Wang, P. Carson","doi":"10.1117/12.2203245","DOIUrl":"https://doi.org/10.1117/12.2203245","url":null,"abstract":"Segmentation of an ultrasound image into functional tissues is of great importance to clinical diagnosis of breast cancer. However, many studies are found to segment only the mass of interest and not all major tissues. Differences and inconsistencies in ultrasound interpretation call for an automated segmentation method to make results operator-independent. Furthermore, manual segmentation of entire three-dimensional (3D) ultrasound volumes is time-consuming, resource-intensive, and clinically impractical. Here, we propose an automated algorithm to segment 3D ultrasound volumes into three major tissue types: cyst/mass, fatty tissue, and fibro-glandular tissue. To test its efficacy and consistency, the proposed automated method was employed on a database of 21 cases of whole breast ultrasound. Experimental results show that our proposed method not only distinguishes fat and non-fat tissues correctly, but performs well in classifying cyst/mass. Comparison of density assessment between the automated method and manual segmentation demonstrates good consistency with an accuracy of 85.7%. Quantitative comparison of corresponding tissue volumes, which uses overlap ratio, gives an average similarity of 74.54%, consistent with values seen in MRI brain segmentations. Thus, our proposed method exhibits great potential as an automated approach to segment 3D whole breast ultrasound volumes into functionally distinct tissues that may help to correct ultrasound speed of sound aberrations and assist in density based prognosis of breast cancer.","PeriodicalId":228011,"journal":{"name":"SPIE Medical Imaging","volume":"87 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":"122384053","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. Rodgers, D. Tessier, D. D'Souza, E. Leung, G. Hajdok, A. Fenster
High-dose-rate (HDR) interstitial brachytherapy is often included in standard-of-care for gynaecological cancers. Needles are currently inserted through a perineal template without any standard real-time imaging modality to assist needle guidance, causing physicians to rely on pre-operative imaging, clinical examination, and experience. While two-dimensional (2D) ultrasound (US) is sometimes used for real-time guidance, visualization of needle placement and depth is difficult and subject to variability and inaccuracy in 2D images. The close proximity to critical organs, in particular the rectum and bladder, can lead to serious complications. We have developed a three-dimensional (3D) transrectal US system and are investigating its use for intra-operative visualization of needle positions used in HDR gynaecological brachytherapy. As a proof-of-concept, four patients were imaged with post-insertion 3D US and x-ray CT. Using software developed in our laboratory, manual rigid registration of the two modalities was performed based on the perineal template’s vaginal cylinder. The needle tip and a second point along the needle path were identified for each needle visible in US. The difference between modalities in the needle trajectory and needle tip position was calculated for each identified needle. For the 60 needles placed, the mean trajectory difference was 3.23 ± 1.65° across the 53 visible needle paths and the mean difference in needle tip position was 3.89 ± 1.92 mm across the 48 visible needles tips. Based on the preliminary results, 3D transrectal US shows potential for the development of a 3D US-based needle guidance system for interstitial gynaecological brachytherapy.
{"title":"Development of 3D ultrasound needle guidance for high-dose-rate interstitial brachytherapy of gynaecological cancers","authors":"J. Rodgers, D. Tessier, D. D'Souza, E. Leung, G. Hajdok, A. Fenster","doi":"10.1117/12.2216546","DOIUrl":"https://doi.org/10.1117/12.2216546","url":null,"abstract":"High-dose-rate (HDR) interstitial brachytherapy is often included in standard-of-care for gynaecological cancers. Needles are currently inserted through a perineal template without any standard real-time imaging modality to assist needle guidance, causing physicians to rely on pre-operative imaging, clinical examination, and experience. While two-dimensional (2D) ultrasound (US) is sometimes used for real-time guidance, visualization of needle placement and depth is difficult and subject to variability and inaccuracy in 2D images. The close proximity to critical organs, in particular the rectum and bladder, can lead to serious complications. We have developed a three-dimensional (3D) transrectal US system and are investigating its use for intra-operative visualization of needle positions used in HDR gynaecological brachytherapy. As a proof-of-concept, four patients were imaged with post-insertion 3D US and x-ray CT. Using software developed in our laboratory, manual rigid registration of the two modalities was performed based on the perineal template’s vaginal cylinder. The needle tip and a second point along the needle path were identified for each needle visible in US. The difference between modalities in the needle trajectory and needle tip position was calculated for each identified needle. For the 60 needles placed, the mean trajectory difference was 3.23 ± 1.65° across the 53 visible needle paths and the mean difference in needle tip position was 3.89 ± 1.92 mm across the 48 visible needles tips. Based on the preliminary results, 3D transrectal US shows potential for the development of a 3D US-based needle guidance system for interstitial gynaecological brachytherapy.","PeriodicalId":228011,"journal":{"name":"SPIE Medical Imaging","volume":"57 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":"122906949","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. Pedrosa, B. Heyde, Laurens Heeren, J. Engvall, J. Zamorano, A. Papachristidis, T. Edvardsen, P. Claus, J. D’hooge
The recent advent of three-dimensional echocardiography has led to an increased interest from the scientific community in left ventricle segmentation frameworks for cardiac volume and function assessment. An automatic orientation of the segmented left ventricular mesh is an important step to obtain a point-to-point correspondence between the mesh and the cardiac anatomy. Furthermore, this would allow for an automatic division of the left ventricle into the standard 17 segments and, thus, fully automatic per-segment analysis, e.g. regional strain assessment. In this work, a method for fully automatic short axis orientation of the segmented left ventricle is presented. The proposed framework aims at detecting the inferior right ventricular insertion point. 211 three-dimensional echocardiographic images were used to validate this framework by comparison to manual annotation of the inferior right ventricular insertion point. A mean unsigned error of 8, 05° ± 18, 50° was found, whereas the mean signed error was 1, 09°. Large deviations between the manual and automatic annotations (> 30°) only occurred in 3, 79% of cases. The average computation time was 666ms in a non-optimized MATLAB environment, which potentiates real-time application. In conclusion, a successful automatic real-time method for orientation of the segmented left ventricle is proposed.
{"title":"Automatic short axis orientation of the left ventricle in 3D ultrasound recordings","authors":"J. Pedrosa, B. Heyde, Laurens Heeren, J. Engvall, J. Zamorano, A. Papachristidis, T. Edvardsen, P. Claus, J. D’hooge","doi":"10.1117/12.2214106","DOIUrl":"https://doi.org/10.1117/12.2214106","url":null,"abstract":"The recent advent of three-dimensional echocardiography has led to an increased interest from the scientific community in left ventricle segmentation frameworks for cardiac volume and function assessment. An automatic orientation of the segmented left ventricular mesh is an important step to obtain a point-to-point correspondence between the mesh and the cardiac anatomy. Furthermore, this would allow for an automatic division of the left ventricle into the standard 17 segments and, thus, fully automatic per-segment analysis, e.g. regional strain assessment. In this work, a method for fully automatic short axis orientation of the segmented left ventricle is presented. The proposed framework aims at detecting the inferior right ventricular insertion point. 211 three-dimensional echocardiographic images were used to validate this framework by comparison to manual annotation of the inferior right ventricular insertion point. A mean unsigned error of 8, 05° ± 18, 50° was found, whereas the mean signed error was 1, 09°. Large deviations between the manual and automatic annotations (> 30°) only occurred in 3, 79% of cases. The average computation time was 666ms in a non-optimized MATLAB environment, which potentiates real-time application. In conclusion, a successful automatic real-time method for orientation of the segmented left ventricle is proposed.","PeriodicalId":228011,"journal":{"name":"SPIE Medical Imaging","volume":"9790 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":"129744409","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}
This paper presents an extension of the classic Conjugate Gradient Algorithm. Motivated by the Analyzer-Based Imaging inverse problem, the novel method maximizes the Poisson regularized log-likelihood with a non-linear transformation of parameter faster than other solutions. The new approach takes advantage of the special properties of the Poisson log-likelihood to conjugate each ascend direction with respect all the previous directions taken by the algorithm. Our solution is compared with the general solution for non-quadratic unconstrained problems: the Polak- Ribiere formula. Both methods are applied to the ABI reconstruction problem.
{"title":"Fast conjugate gradient algorithm extension for analyzer-based imaging reconstruction","authors":"Oriol Caudevilla, J. Brankov","doi":"10.1117/12.2217164","DOIUrl":"https://doi.org/10.1117/12.2217164","url":null,"abstract":"This paper presents an extension of the classic Conjugate Gradient Algorithm. Motivated by the Analyzer-Based Imaging inverse problem, the novel method maximizes the Poisson regularized log-likelihood with a non-linear transformation of parameter faster than other solutions. The new approach takes advantage of the special properties of the Poisson log-likelihood to conjugate each ascend direction with respect all the previous directions taken by the algorithm. Our solution is compared with the general solution for non-quadratic unconstrained problems: the Polak- Ribiere formula. Both methods are applied to the ABI reconstruction problem.","PeriodicalId":228011,"journal":{"name":"SPIE Medical Imaging","volume":"1 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":"129235123","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}
Scanning probe acoustic microscope (SPAM) can be used to acquire the morphology image as well as the non-destructive internal structures acoustic image. However, the observations of the morphology image as well as the internal structures acoustic image of liver cancer cells in SPAM are few. In this paper, we cultured 4 different types of liver cancer cells on the silicon wafer and coverslip to observe their morphology images as well as acoustic images in SPAM, and made a preliminary study of the 8 types of cells specimens (hereinafter referred to as the silicon specimens and coverslips specimens). The experimental measurement results showed that some cellular pseudopodium were observed in the morphology images of the coverslip specimens while no such cellular pseupodium were appeared in the morphology images of the silicon specimens, which concluded that the living liver cancer cells were less likely to grow on the silicon wafer. SPAM provides a rapid and sensitive visual method for studying the morphology and internal structures of the cancer cells. The proposed method can be also used to obtain the morphology and internal information in both solid and soft material wafers, such as silicon and cells, with the resolution of nanometer scale.
{"title":"Observations of liver cancer cells in scanning probe acoustic microscope: a preliminary study","authors":"Xiaohui Chen, Xiaoyue Fang, Qing Xi, Hua Guo, Ning Zhang, Mingyue Ding","doi":"10.1117/12.2214333","DOIUrl":"https://doi.org/10.1117/12.2214333","url":null,"abstract":"Scanning probe acoustic microscope (SPAM) can be used to acquire the morphology image as well as the non-destructive internal structures acoustic image. However, the observations of the morphology image as well as the internal structures acoustic image of liver cancer cells in SPAM are few. In this paper, we cultured 4 different types of liver cancer cells on the silicon wafer and coverslip to observe their morphology images as well as acoustic images in SPAM, and made a preliminary study of the 8 types of cells specimens (hereinafter referred to as the silicon specimens and coverslips specimens). The experimental measurement results showed that some cellular pseudopodium were observed in the morphology images of the coverslip specimens while no such cellular pseupodium were appeared in the morphology images of the silicon specimens, which concluded that the living liver cancer cells were less likely to grow on the silicon wafer. SPAM provides a rapid and sensitive visual method for studying the morphology and internal structures of the cancer cells. The proposed method can be also used to obtain the morphology and internal information in both solid and soft material wafers, such as silicon and cells, with the resolution of nanometer scale.","PeriodicalId":228011,"journal":{"name":"SPIE Medical Imaging","volume":"83 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":"123224436","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}
One technique used to infer and monitor patient's respiratory conditions is the electrical impedance tomography (EIT). This provides images with information about lung function. The EIT image contrast is dependent on the variation of electrical impedance, therefore, this image does not provide anatomical details in border regions of several organs. To contribute to a clinical solution, we propose a new method to delimit regions of interest such as the pulmonary region and to improve the reconstruction quality of the EIT. Using a Matlab Toolbox k-wave, the ultrasound propagation phenomenon in homogeneous medium without patient (Reference) and with thoracic models were simulated, separately via a set of several ultrasound transducers distributed around the chest. After pulse emission by a transducer (TR), all received signals were compared considering the two sets of signals. If the energy relation between parts of the signals does not exceed an empirical threshold (30% in this study), a partial mask is generated between the transmitter and the receptor. This process was repeated until all 128 transducers are considered as TR-emitters. The 128 transducers (150kHz) are uniformly distributed. The evaluation was made by visually comparing the resulting images with the respective simulated object. A simple approach was presented to delimit high contrast organs with ultrasound transducers distributed around the patient. This approach allows other lower contrast objects to become invisible by varying the threshold limit. The investigation, based on numerical simulations of ultrasonic propagation, has shown promising results in the delimitation of the pulmonary region.
{"title":"Delimitation of the lung region with distributed ultrasound transducers","authors":"D. A. Cardona Cárdenas, S. Furuie","doi":"10.1117/12.2216811","DOIUrl":"https://doi.org/10.1117/12.2216811","url":null,"abstract":"One technique used to infer and monitor patient's respiratory conditions is the electrical impedance tomography (EIT). This provides images with information about lung function. The EIT image contrast is dependent on the variation of electrical impedance, therefore, this image does not provide anatomical details in border regions of several organs. To contribute to a clinical solution, we propose a new method to delimit regions of interest such as the pulmonary region and to improve the reconstruction quality of the EIT. Using a Matlab Toolbox k-wave, the ultrasound propagation phenomenon in homogeneous medium without patient (Reference) and with thoracic models were simulated, separately via a set of several ultrasound transducers distributed around the chest. After pulse emission by a transducer (TR), all received signals were compared considering the two sets of signals. If the energy relation between parts of the signals does not exceed an empirical threshold (30% in this study), a partial mask is generated between the transmitter and the receptor. This process was repeated until all 128 transducers are considered as TR-emitters. The 128 transducers (150kHz) are uniformly distributed. The evaluation was made by visually comparing the resulting images with the respective simulated object. A simple approach was presented to delimit high contrast organs with ultrasound transducers distributed around the patient. This approach allows other lower contrast objects to become invisible by varying the threshold limit. The investigation, based on numerical simulations of ultrasonic propagation, has shown promising results in the delimitation of the pulmonary region.","PeriodicalId":228011,"journal":{"name":"SPIE Medical Imaging","volume":"1 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":"114766814","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}
M. Seifert, C. Hauke, F. Horn, Sebastian Lachner, V. Ludwig, G. Pelzer, J. Rieger, M. Schuster, Johannes Wandner, A. Wolf, T. Michel, G. Anton
X-ray grating-based phase-contrast imaging might open up entirely new opportunities in medical imaging. However, transferring the interferometer technique from laboratory setups to conventional imaging systems the necessary rigidity of the system is difficult to achieve. Therefore, vibrations or distortions of the system lead to inaccuracies within the phase-stepping procedure. Given insufficient stability of the phase-step positions, up to now, artifacts in phase-contrast images occur, which lower the image quality. This is a problem with regard to the intended use of phase-contrast imaging in clinical routine as for example tiny structures of the human anatomy cannot be observed. In this contribution we evaluate an algorithm proposed by Vargas et.al.1 and applied to X-ray imaging by Pelzer et.al. that enables us to reconstruct a differential phase-contrast image without the knowledge of the specific phase-step positions. This method was tested in comparison to the standard reconstruction by Fourier analysis. The quality of phase-contrast images remains stable, even if the phase-step positions are completely unknown and not uniformly distributed. To also achieve attenuation and dark-field images the proposed algorithm has been combined with a further algorithm of Vargas et al.3 Using this algorithm, the phase-step positions can be reconstructed. With the help of the proper phase-step positions it is possible to get information about the phase, the amplitude and the offset of the measured data. We evaluated this algorithm concerning the measurement of thick objects which show a high absorbency.
{"title":"Evaluation of a new reconstruction algorithm for x-ray phase-contrast imaging","authors":"M. Seifert, C. Hauke, F. Horn, Sebastian Lachner, V. Ludwig, G. Pelzer, J. Rieger, M. Schuster, Johannes Wandner, A. Wolf, T. Michel, G. Anton","doi":"10.1117/12.2216874","DOIUrl":"https://doi.org/10.1117/12.2216874","url":null,"abstract":"X-ray grating-based phase-contrast imaging might open up entirely new opportunities in medical imaging. However, transferring the interferometer technique from laboratory setups to conventional imaging systems the necessary rigidity of the system is difficult to achieve. Therefore, vibrations or distortions of the system lead to inaccuracies within the phase-stepping procedure. Given insufficient stability of the phase-step positions, up to now, artifacts in phase-contrast images occur, which lower the image quality. This is a problem with regard to the intended use of phase-contrast imaging in clinical routine as for example tiny structures of the human anatomy cannot be observed. In this contribution we evaluate an algorithm proposed by Vargas et.al.1 and applied to X-ray imaging by Pelzer et.al. that enables us to reconstruct a differential phase-contrast image without the knowledge of the specific phase-step positions. This method was tested in comparison to the standard reconstruction by Fourier analysis. The quality of phase-contrast images remains stable, even if the phase-step positions are completely unknown and not uniformly distributed. To also achieve attenuation and dark-field images the proposed algorithm has been combined with a further algorithm of Vargas et al.3 Using this algorithm, the phase-step positions can be reconstructed. With the help of the proper phase-step positions it is possible to get information about the phase, the amplitude and the offset of the measured data. We evaluated this algorithm concerning the measurement of thick objects which show a high absorbency.","PeriodicalId":228011,"journal":{"name":"SPIE Medical Imaging","volume":"1 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":"128019665","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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