Yaron Anavi, I. Kogan, Elad Gelbart, O. Geva, H. Greenspan
We explore the combination of text metadata, such as patients’ age and gender, with image-based features, for X-ray chest pathology image retrieval. We focus on a feature set extracted from a pre-trained deep convolutional network shown in earlier work to achieve state-of-the-art results. Two distance measures are explored: a descriptor-based measure, which computes the distance between image descriptors, and a classification-based measure, which performed by a comparison of the corresponding SVM classification probabilities. We show that retrieval results increase once the age and gender information combined with the features extracted from the last layers of the network, with best results using the classification-based scheme. Visualization of the X-ray data is presented by embedding the high dimensional deep learning features in a 2-D dimensional space while preserving the pairwise distances using the t-SNE algorithm. The 2-D visualization gives the unique ability to find groups of X-ray images that are similar to the query image and among themselves, which is a characteristic we do not see in a 1-D traditional ranking.
{"title":"Visualizing and enhancing a deep learning framework using patients age and gender for chest x-ray image retrieval","authors":"Yaron Anavi, I. Kogan, Elad Gelbart, O. Geva, H. Greenspan","doi":"10.1117/12.2217587","DOIUrl":"https://doi.org/10.1117/12.2217587","url":null,"abstract":"We explore the combination of text metadata, such as patients’ age and gender, with image-based features, for X-ray chest pathology image retrieval. We focus on a feature set extracted from a pre-trained deep convolutional network shown in earlier work to achieve state-of-the-art results. Two distance measures are explored: a descriptor-based measure, which computes the distance between image descriptors, and a classification-based measure, which performed by a comparison of the corresponding SVM classification probabilities. We show that retrieval results increase once the age and gender information combined with the features extracted from the last layers of the network, with best results using the classification-based scheme. Visualization of the X-ray data is presented by embedding the high dimensional deep learning features in a 2-D dimensional space while preserving the pairwise distances using the t-SNE algorithm. The 2-D visualization gives the unique ability to find groups of X-ray images that are similar to the query image and among themselves, which is a characteristic we do not see in a 1-D traditional ranking.","PeriodicalId":228011,"journal":{"name":"SPIE Medical Imaging","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129986578","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}
Over the past decade, there has been an increasing focus on quantitative imaging biomarkers (QIBs), which are defined as “objectively measured characteristics derived from in vivo images as indicators of normal biological processes, pathogenic processes, or response to a therapeutic intervention”1. To evolve qualitative imaging assessments to the use of QIBs requires the development and standardization of data acquisition, data analysis, and data display techniques, as well as appropriate reporting structures. As such, successful implementation of QIB applications relies heavily on expertise from the fields of medical physics, radiology, statistics, and informatics as well as collaboration from vendors of imaging acquisition, analysis, and reporting systems. When successfully implemented, QIBs will provide image-derived metrics with known bias and variance that can be validated with anatomically and physiologically relevant measures, including treatment response (and the heterogeneity of that response) and outcome. Such non-invasive quantitative measures can then be used effectively in clinical and translational research and will contribute significantly to the goals of precision medicine. This presentation will focus on 1) outlining the opportunities for QIB applications, with examples to demonstrate applications in both research and patient care, 2) discussing key challenges in the implementation of QIB applications, and 3) providing overviews of efforts to address such challenges from federal, scientific, and professional organizations, including, but not limited to, the RSNA, NCI, FDA, and NIST. 1Sullivan, Obuchowski, Kessler, et al. Radiology, epub August 2015.
{"title":"The evolution of medical imaging from qualitative to quantitative: opportunities, challenges, and approaches (Conference Presentation)","authors":"E. Jackson","doi":"10.1117/12.2228332","DOIUrl":"https://doi.org/10.1117/12.2228332","url":null,"abstract":"Over the past decade, there has been an increasing focus on quantitative imaging biomarkers (QIBs), which are defined as “objectively measured characteristics derived from in vivo images as indicators of normal biological processes, pathogenic processes, or response to a therapeutic intervention”1. To evolve qualitative imaging assessments to the use of QIBs requires the development and standardization of data acquisition, data analysis, and data display techniques, as well as appropriate reporting structures. As such, successful implementation of QIB applications relies heavily on expertise from the fields of medical physics, radiology, statistics, and informatics as well as collaboration from vendors of imaging acquisition, analysis, and reporting systems. When successfully implemented, QIBs will provide image-derived metrics with known bias and variance that can be validated with anatomically and physiologically relevant measures, including treatment response (and the heterogeneity of that response) and outcome. Such non-invasive quantitative measures can then be used effectively in clinical and translational research and will contribute significantly to the goals of precision medicine. This presentation will focus on 1) outlining the opportunities for QIB applications, with examples to demonstrate applications in both research and patient care, 2) discussing key challenges in the implementation of QIB applications, and 3) providing overviews of efforts to address such challenges from federal, scientific, and professional organizations, including, but not limited to, the RSNA, NCI, FDA, and NIST. 1Sullivan, Obuchowski, Kessler, et al. Radiology, epub August 2015.","PeriodicalId":228011,"journal":{"name":"SPIE Medical Imaging","volume":"9783 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130789947","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}
Positron emission tomography (PET) is the highest sensitivity technique for human whole-body imaging studies. However, current clinical PET scanners do not make full use of the available signal, as they only permit imaging of a 15-25 cm segment of the body at one time. Given the limited sensitive region, whole-body imaging with clinical PET scanners requires relatively long scan times and subjects the patient to higher than necessary radiation doses. The EXPLORER initiative aims to build a 2-meter axial length PET scanner to allow imaging the entire subject at once, capturing nearly the entire available PET signal. EXPLORER will acquire data with ~40-fold greater sensitivity leading to a six-fold increase in reconstructed signal-to-noise ratio for imaging the total body. Alternatively, total-body images with the EXPLORER scanner will be able to be acquired in ~30 seconds or with ~0.15 mSv injected dose, while maintaining current PET image quality. The superior sensitivity will open many new avenues for biomedical research. Specifically for cancer applications, high sensitivity PET will enable detection of smaller lesions. Additionally, greater sensitivity will allow imaging out to 10 half-lives of positron emitting radiotracers. This will enable 1) metabolic ultra-staging with FDG by extending the uptake and clearance time to 3-5 hours to significantly improve contrast and 2) improved kinetic imaging with short-lived radioisotopes such as C-11, crucial for drug development studies. Frequent imaging studies of the same subject to study disease progression or to track response to therapy will be possible with the low dose capabilities of the EXPLORER scanner. The low dose capabilities will also open up new imaging possibilities in pediatrics and adolescents to better study developmental disorders. This talk will review the basis for developing total-body PET, potential applications, and review progress to date in developing EXPLORER, the first total-body PET scanner.
{"title":"EXPLORER: Changing the molecular imaging paradigm with total-body PET/CT (Conference Presentation)","authors":"S. Cherry, R. Badawi, T. Jones","doi":"10.1117/12.2227151","DOIUrl":"https://doi.org/10.1117/12.2227151","url":null,"abstract":"Positron emission tomography (PET) is the highest sensitivity technique for human whole-body imaging studies. However, current clinical PET scanners do not make full use of the available signal, as they only permit imaging of a 15-25 cm segment of the body at one time. Given the limited sensitive region, whole-body imaging with clinical PET scanners requires relatively long scan times and subjects the patient to higher than necessary radiation doses. The EXPLORER initiative aims to build a 2-meter axial length PET scanner to allow imaging the entire subject at once, capturing nearly the entire available PET signal. EXPLORER will acquire data with ~40-fold greater sensitivity leading to a six-fold increase in reconstructed signal-to-noise ratio for imaging the total body. Alternatively, total-body images with the EXPLORER scanner will be able to be acquired in ~30 seconds or with ~0.15 mSv injected dose, while maintaining current PET image quality. The superior sensitivity will open many new avenues for biomedical research. Specifically for cancer applications, high sensitivity PET will enable detection of smaller lesions. Additionally, greater sensitivity will allow imaging out to 10 half-lives of positron emitting radiotracers. This will enable 1) metabolic ultra-staging with FDG by extending the uptake and clearance time to 3-5 hours to significantly improve contrast and 2) improved kinetic imaging with short-lived radioisotopes such as C-11, crucial for drug development studies. Frequent imaging studies of the same subject to study disease progression or to track response to therapy will be possible with the low dose capabilities of the EXPLORER scanner. The low dose capabilities will also open up new imaging possibilities in pediatrics and adolescents to better study developmental disorders. This talk will review the basis for developing total-body PET, potential applications, and review progress to date in developing EXPLORER, the first total-body PET scanner.","PeriodicalId":228011,"journal":{"name":"SPIE Medical Imaging","volume":"os-52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127793034","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}
Ultrasound-guided needle tracking systems are frequently used in surgical procedures. Various needle tracking technologies have been developed using ultrasound, electromagnetic sensors, and optical sensors. To evaluate these new needle tracking technologies, 3D volume information is often acquired to compute the actual distance from the needle tip to the target object. The image-guidance conditions for comparison are often inconsistent due to the ultrasound beam-thickness. Since 3D volumes are necessary, there is often some time delay between the surgical procedure and the evaluation. These evaluation methods will generally only measure the final needle location because they interrupt the surgical procedure. The main contribution of this work is a new platform for evaluating needle tracking systems in real-time, resolving the problems stated above. We developed new tools to evaluate the precise distance between the needle tip and the target object. A PZT element transmitting unit is designed as needle introducer shape so that it can be inserted in the needle. We have collected time of flight and amplitude information in real-time. We propose two systems to collect ultrasound signals. We demonstrate this platform on an ultrasound DAQ system and a cost-effective FPGA board. The results of a chicken breast experiment show the feasibility of tracking a time series of needle tip distances. We performed validation experiments with a plastisol phantom and have shown that the preliminary data fits a linear regression model with a RMSE of less than 0.6mm. Our platform can be applied to more general needle tracking methods using other forms of guidance.
{"title":"New platform for evaluating ultrasound-guided interventional technologies","authors":"Younsu Kim, Xiaoyu Guo, E. Boctor","doi":"10.1117/12.2217242","DOIUrl":"https://doi.org/10.1117/12.2217242","url":null,"abstract":"Ultrasound-guided needle tracking systems are frequently used in surgical procedures. Various needle tracking technologies have been developed using ultrasound, electromagnetic sensors, and optical sensors. To evaluate these new needle tracking technologies, 3D volume information is often acquired to compute the actual distance from the needle tip to the target object. The image-guidance conditions for comparison are often inconsistent due to the ultrasound beam-thickness. Since 3D volumes are necessary, there is often some time delay between the surgical procedure and the evaluation. These evaluation methods will generally only measure the final needle location because they interrupt the surgical procedure. The main contribution of this work is a new platform for evaluating needle tracking systems in real-time, resolving the problems stated above. We developed new tools to evaluate the precise distance between the needle tip and the target object. A PZT element transmitting unit is designed as needle introducer shape so that it can be inserted in the needle. We have collected time of flight and amplitude information in real-time. We propose two systems to collect ultrasound signals. We demonstrate this platform on an ultrasound DAQ system and a cost-effective FPGA board. The results of a chicken breast experiment show the feasibility of tracking a time series of needle tip distances. We performed validation experiments with a plastisol phantom and have shown that the preliminary data fits a linear regression model with a RMSE of less than 0.6mm. Our platform can be applied to more general needle tracking methods using other forms of guidance.","PeriodicalId":228011,"journal":{"name":"SPIE Medical Imaging","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125546660","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}
Controlling the thermal dose during ablation therapy is instrumental to successfully removing the tumor while preserving the surrounding healthy tissue. In the practical scenario, surgeons must be able to determine the ablation completeness in the tumor region. Various methods have been proposed to monitor it, one of which uses ultrasound since it is a common intraoperative imaging modality due to its non-invasive, cost-effective, and convenient natures. In our approach, we propose to use time of flight (ToF) information to estimate speed of sound changes. Accurate speed of sound estimation is crucial because it is directly correlated with temperature change and subsequent determination of ablation completeness. We divide the region of interest in a circular fashion with a variable radius from the ablator tip. We introduce the concept of effective speed of sound in each of the sub-regions. Our active PZT element control system facilitates this unique approach by allowing us to acquire one-way ToF information between the PZT element and each of the ultrasound elements. We performed a simulation and an experiment to verify feasibility of this method. The simulation result showed that we could compute the effective speed of sound within 0.02m/s error in our discrete model. We also perform a sensitivity analysis for this model. Most of the experimental results had less than 1% error. Simulation using a Gaussian continuous model with multiple PZT elements is also demonstrated. We simulate the effect of the element location one the optimization result.
{"title":"Speed of sound estimation with active PZT element for thermal monitoring during ablation therapy: feasibility study","authors":"Younsu Kim, Xiaoyu Guo, Alexis Cheng, E. Boctor","doi":"10.1117/12.2217086","DOIUrl":"https://doi.org/10.1117/12.2217086","url":null,"abstract":"Controlling the thermal dose during ablation therapy is instrumental to successfully removing the tumor while preserving the surrounding healthy tissue. In the practical scenario, surgeons must be able to determine the ablation completeness in the tumor region. Various methods have been proposed to monitor it, one of which uses ultrasound since it is a common intraoperative imaging modality due to its non-invasive, cost-effective, and convenient natures. In our approach, we propose to use time of flight (ToF) information to estimate speed of sound changes. Accurate speed of sound estimation is crucial because it is directly correlated with temperature change and subsequent determination of ablation completeness. We divide the region of interest in a circular fashion with a variable radius from the ablator tip. We introduce the concept of effective speed of sound in each of the sub-regions. Our active PZT element control system facilitates this unique approach by allowing us to acquire one-way ToF information between the PZT element and each of the ultrasound elements. We performed a simulation and an experiment to verify feasibility of this method. The simulation result showed that we could compute the effective speed of sound within 0.02m/s error in our discrete model. We also perform a sensitivity analysis for this model. Most of the experimental results had less than 1% error. Simulation using a Gaussian continuous model with multiple PZT elements is also demonstrated. We simulate the effect of the element location one the optimization result.","PeriodicalId":228011,"journal":{"name":"SPIE Medical Imaging","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132488280","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}
Wanyi Fu, X. Tian, G. Sturgeon, G. Agasthya, W. Segars, M. Goodsitt, E. Kazerooni, E. Samei
In thoracic CT, organ-based tube current modulation (OTCM) reduces breast dose by lowering the tube current in the 120° anterior dose reduction zone of patients. However, in practice the breasts usually expand to an angle larger than the dose reduction zone. This work aims to simulate a breast positioning technique (BPT) to constrain the breast tissue to within the dose reduction zone for OTCM and to evaluate the corresponding potential reduction in breast dose. Thirteen female anthropomorphic computational phantoms were studied (age range: 27-65 y.o., weight range: 52-105.8 kg). Each phantom was modeled in the supine position with and without application of the BPT. Attenuation-based tube current (ATCM, reference mA) was generated by a ray-tracing program, taking into account the patient attenuation change in the longitudinal and angular plane (CAREDose4D, Siemens Healthcare). OTCM was generated by reducing the mA to 20% between ± 60° anterior of the patient and increasing the mA in the remaining projections correspondingly (X-CARE, Siemens Healthcare) to maintain the mean tube current. Breast tissue dose was estimated using a validated Monte Carlo program for a commercial scanner (SOMATOM Definition Flash, Siemens Healthcare). Compared to standard tube current modulation, breast dose was significantly reduced using OTCM by 19.8±4.7%. With the BPT, breast dose was reduced by an additional 20.4±6.5% to 37.1±6.9%, using the same CTDIvol. BPT was more effective for phantoms simulating women with larger breasts with the average breast dose reduction of 30.2%, 39.2%, and 49.2% from OTCMBP to ATCM, using the same CTDIvol for phantoms with 0.5, 1.5, and 2.5 kg breasts, respectively. This study shows that a specially designed BPT improves the effectiveness of OTCM.
{"title":"Estimation of breast dose saving potential using a breast positioning technique for organ-based tube current modulated CT","authors":"Wanyi Fu, X. Tian, G. Sturgeon, G. Agasthya, W. Segars, M. Goodsitt, E. Kazerooni, E. Samei","doi":"10.1117/12.2217239","DOIUrl":"https://doi.org/10.1117/12.2217239","url":null,"abstract":"In thoracic CT, organ-based tube current modulation (OTCM) reduces breast dose by lowering the tube current in the 120° anterior dose reduction zone of patients. However, in practice the breasts usually expand to an angle larger than the dose reduction zone. This work aims to simulate a breast positioning technique (BPT) to constrain the breast tissue to within the dose reduction zone for OTCM and to evaluate the corresponding potential reduction in breast dose. Thirteen female anthropomorphic computational phantoms were studied (age range: 27-65 y.o., weight range: 52-105.8 kg). Each phantom was modeled in the supine position with and without application of the BPT. Attenuation-based tube current (ATCM, reference mA) was generated by a ray-tracing program, taking into account the patient attenuation change in the longitudinal and angular plane (CAREDose4D, Siemens Healthcare). OTCM was generated by reducing the mA to 20% between ± 60° anterior of the patient and increasing the mA in the remaining projections correspondingly (X-CARE, Siemens Healthcare) to maintain the mean tube current. Breast tissue dose was estimated using a validated Monte Carlo program for a commercial scanner (SOMATOM Definition Flash, Siemens Healthcare). Compared to standard tube current modulation, breast dose was significantly reduced using OTCM by 19.8±4.7%. With the BPT, breast dose was reduced by an additional 20.4±6.5% to 37.1±6.9%, using the same CTDIvol. BPT was more effective for phantoms simulating women with larger breasts with the average breast dose reduction of 30.2%, 39.2%, and 49.2% from OTCMBP to ATCM, using the same CTDIvol for phantoms with 0.5, 1.5, and 2.5 kg breasts, respectively. This study shows that a specially designed BPT improves the effectiveness of OTCM.","PeriodicalId":228011,"journal":{"name":"SPIE Medical Imaging","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121038100","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}
The purpose of this work was to test the ability of visual-search (VS) model observers to predict the lesion- detection performance of human observers with hybrid SPECT images. These images consist of clinical back- grounds with simulated abnormalities. The application of existing scanning model observers to hybrid images is complicated by the need for extensive statistical information, whereas VS models based on separate search and analysis processes may operate with reduced knowledge. A localization ROC (LROC) study involved the detection and localization of solitary pulmonary nodules in Tc-99m lung images. The study was aimed at op- timizing the number of iterations and the postfiltering of four rescaled block-iterative reconstruction strategies. These strategies implemented different combinations of attenuation correction, scatter correction, and detector resolution correction. For a VS observer in this study, the search and analysis processes were guided by a single set of base morphological features derived from knowledge of the lesion profile. One base set used difference-of- Gaussian channels while a second base set implemented spatial derivatives in combination with the Burgess eye filter. A feature-adaptive VS observer selected features of interest for a given image set on the basis of training-set performance. A comparison of the feature-adaptive observer results against previously acquired human-observer data is presented.
{"title":"Visual-search observers for SPECT simulations with clinical backgrounds","authors":"H. Gifford","doi":"10.1117/12.2217716","DOIUrl":"https://doi.org/10.1117/12.2217716","url":null,"abstract":"The purpose of this work was to test the ability of visual-search (VS) model observers to predict the lesion- detection performance of human observers with hybrid SPECT images. These images consist of clinical back- grounds with simulated abnormalities. The application of existing scanning model observers to hybrid images is complicated by the need for extensive statistical information, whereas VS models based on separate search and analysis processes may operate with reduced knowledge. A localization ROC (LROC) study involved the detection and localization of solitary pulmonary nodules in Tc-99m lung images. The study was aimed at op- timizing the number of iterations and the postfiltering of four rescaled block-iterative reconstruction strategies. These strategies implemented different combinations of attenuation correction, scatter correction, and detector resolution correction. For a VS observer in this study, the search and analysis processes were guided by a single set of base morphological features derived from knowledge of the lesion profile. One base set used difference-of- Gaussian channels while a second base set implemented spatial derivatives in combination with the Burgess eye filter. A feature-adaptive VS observer selected features of interest for a given image set on the basis of training-set performance. A comparison of the feature-adaptive observer results against previously acquired human-observer data is presented.","PeriodicalId":228011,"journal":{"name":"SPIE Medical Imaging","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117043337","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}
X-ray phase contrast imaging has been investigated during the last two decades for potential benefits in soft tissue imaging. Long imaging time, high radiation dose and general measurement complexity involving motion of x-ray optical components have prevented the clinical translation of these methods. In all existing popular phase contrast imaging methods, multiple measurements per projection angle involving motion of optical components are required to achieve quantitatively accurate estimation of absorption, phase and differential phase. Recently we proposed an algorithmic approach to use spectral detection data in a phase contrast imaging setup to obtain absorption, phase and differential phase in a single-step. Our generic approach has been shown via simulations in all three types of phase contrast imaging: propagation, coded aperture and grating interferometry. While other groups have used spectral detector in phase contrast imaging setups, our proposed method is unique in outlining an approach to use this spectral data to simplify phase contrast imaging. In this abstract we show the first experimental proof of our single-shot phase retrieval using a Medipix3 photon counting detector in an edge illumination aperture (also referred to as coded aperture) phase contrast set up as well as for a free space propagation setup. Our preliminary results validate our new transport equation for edge illumination PCI and our spectral phase retrieval algorithm for both PCI methods being investigated. Comparison with simulations also point to excellent performance of Medipix3 built-in charge sharing correction mechanism.
{"title":"Single-shot x-ray phase contrast imaging with an algorithmic approach using spectral detection","authors":"M. Das, Chan-Soo Park, N. Fredette","doi":"10.1117/12.2218056","DOIUrl":"https://doi.org/10.1117/12.2218056","url":null,"abstract":"X-ray phase contrast imaging has been investigated during the last two decades for potential benefits in soft tissue imaging. Long imaging time, high radiation dose and general measurement complexity involving motion of x-ray optical components have prevented the clinical translation of these methods. In all existing popular phase contrast imaging methods, multiple measurements per projection angle involving motion of optical components are required to achieve quantitatively accurate estimation of absorption, phase and differential phase. Recently we proposed an algorithmic approach to use spectral detection data in a phase contrast imaging setup to obtain absorption, phase and differential phase in a single-step. Our generic approach has been shown via simulations in all three types of phase contrast imaging: propagation, coded aperture and grating interferometry. While other groups have used spectral detector in phase contrast imaging setups, our proposed method is unique in outlining an approach to use this spectral data to simplify phase contrast imaging. In this abstract we show the first experimental proof of our single-shot phase retrieval using a Medipix3 photon counting detector in an edge illumination aperture (also referred to as coded aperture) phase contrast set up as well as for a free space propagation setup. Our preliminary results validate our new transport equation for edge illumination PCI and our spectral phase retrieval algorithm for both PCI methods being investigated. Comparison with simulations also point to excellent performance of Medipix3 built-in charge sharing correction mechanism.","PeriodicalId":228011,"journal":{"name":"SPIE Medical Imaging","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128025184","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}
Synthetic aperture for ultrasound is a technique utilizing a wide aperture in both transmit and receive to enhance the ultrasound image quality. The limitation of synthetic aperture is the maximum available aperture size limit determined by the physical size of ultrasound probe. We propose Synthetic-Tracked Aperture Ultrasound (STRATUS) imaging system to overcome the limitation by extending the beamforming aperture size through ultrasound probe tracking. With a setup involving a robotic arm, the ultrasound probe is moved using the robotic arm, while the positions on a scanning trajectory are tracked in real-time. Data from each pose are synthesized to construct a high resolution image. In previous studies, we have demonstrated the feasibility through phantom experiments. However, various additional factors such as real-time data collection or motion artifacts should be taken into account when the in vivo target becomes the subject. In this work, we build a robot-based STRATUS imaging system with continuous data collection capability considering the practical implementation. A curvilinear array is used instead of a linear array to benefit from its wider capture angle. We scanned human forearms under two scenarios: one submerged the arm in the water tank under 10 cm depth, and the other directly scanned the arm from the surface. The image contrast improved 5.51 dB, and 9.96 dB for the underwater scan and the direct scan, respectively. The result indicates the practical feasibility of STRATUS imaging system, and the technique can be potentially applied to the wide range of human body.
{"title":"In vivo visualization of robotically implemented synthetic tracked aperture ultrasound (STRATUS) imaging system using curvilinear array","authors":"Haichong K. Zhang, F. Aalamifar, E. Boctor","doi":"10.1117/12.2217278","DOIUrl":"https://doi.org/10.1117/12.2217278","url":null,"abstract":"Synthetic aperture for ultrasound is a technique utilizing a wide aperture in both transmit and receive to enhance the ultrasound image quality. The limitation of synthetic aperture is the maximum available aperture size limit determined by the physical size of ultrasound probe. We propose Synthetic-Tracked Aperture Ultrasound (STRATUS) imaging system to overcome the limitation by extending the beamforming aperture size through ultrasound probe tracking. With a setup involving a robotic arm, the ultrasound probe is moved using the robotic arm, while the positions on a scanning trajectory are tracked in real-time. Data from each pose are synthesized to construct a high resolution image. In previous studies, we have demonstrated the feasibility through phantom experiments. However, various additional factors such as real-time data collection or motion artifacts should be taken into account when the in vivo target becomes the subject. In this work, we build a robot-based STRATUS imaging system with continuous data collection capability considering the practical implementation. A curvilinear array is used instead of a linear array to benefit from its wider capture angle. We scanned human forearms under two scenarios: one submerged the arm in the water tank under 10 cm depth, and the other directly scanned the arm from the surface. The image contrast improved 5.51 dB, and 9.96 dB for the underwater scan and the direct scan, respectively. The result indicates the practical feasibility of STRATUS imaging system, and the technique can be potentially applied to the wide range of human body.","PeriodicalId":228011,"journal":{"name":"SPIE Medical Imaging","volume":"190 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123385841","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}
Yang Chen, Ke Li, Yinsheng Li, J. Hsieh, Guang-Hong Chen
When the scan field of view (SFOV) of a CT system is not large enough to enclose the entire cross-section of a patient, or the patient needs to be intentionally positioned partially outside the SFOV for certain clinical CT scans, truncation artifacts are often observed in the reconstructed CT images. Conventional wisdom to reduce truncation artifacts is to complete the truncated projection data via data extrapolation with different a priori assumptions. This paper presents a novel truncation artifact reduction method that directly works in the CT image domain. Specifically, a discriminative dictionary that includes a sub-dictionary of truncation artifacts and a sub-dictionary of non-artifact image information was used to separate a truncation artifact-contaminated image into two sub-images, one with reduced truncation artifacts, and the other one containing only the truncation artifacts. Both experimental phantom and retrospective human subject studies have been performed to characterize the performance of the proposed truncation artifact reduction method.
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