Pub Date : 2013-10-01DOI: 10.1109/ICMIPE.2013.6864533
Z. Ying, Wang Zehua, Zhang Chi, Yang Yang, N. Simha, Li Deyu
Invasive incisions are inevitable in cardiac surgeries. It is clinical significant to explore the optimal locations of the incisions. What is more, the deformation of pectoralis major affects the proper healing of wounds in the patients with invasive surgery on the chest. Ultrasound, with the advantages of portability, non-invasiveness and no radiation, becomes a common method to measure the structural information of the human tissue in vivo. In this study, the deformation of pectoralis major was measured in real-time by the M-mode ultrasound signal acquisition device which can fasten the probe on the chest. The regularity of muscle deformation may provide basis for the choice of the incision position in surgical planning, as well as the optimization of rehabilitation exercises.
{"title":"Measurement of pectoralis major deformation during activities with M-mode ultrasound","authors":"Z. Ying, Wang Zehua, Zhang Chi, Yang Yang, N. Simha, Li Deyu","doi":"10.1109/ICMIPE.2013.6864533","DOIUrl":"https://doi.org/10.1109/ICMIPE.2013.6864533","url":null,"abstract":"Invasive incisions are inevitable in cardiac surgeries. It is clinical significant to explore the optimal locations of the incisions. What is more, the deformation of pectoralis major affects the proper healing of wounds in the patients with invasive surgery on the chest. Ultrasound, with the advantages of portability, non-invasiveness and no radiation, becomes a common method to measure the structural information of the human tissue in vivo. In this study, the deformation of pectoralis major was measured in real-time by the M-mode ultrasound signal acquisition device which can fasten the probe on the chest. The regularity of muscle deformation may provide basis for the choice of the incision position in surgical planning, as well as the optimization of rehabilitation exercises.","PeriodicalId":135461,"journal":{"name":"2013 IEEE International Conference on Medical Imaging Physics and Engineering","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126300838","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}
Pub Date : 2013-10-01DOI: 10.1109/ICMIPE.2013.6864556
Xing Ming, Longjun He, Qian Liu
Efficient assessment of vascular structures plays a significant role in many medical procedures. We present a practical approach to segmentation of vascular tree in angiography images. It is implemented in an interactive 3D visualization-assisted system and consists of the following main steps. First, angiography image is filtered to enhance vessels and eliminate irrelevant structures. Second, the centerline and thickness of the vessel are extracted utilizes a novel local tracking algorithm named adaptive sampling. The sampling starts from a single seed point and marches recursively forward along possible vessel continuations to capture whole tree-like structure, in which the branch detection and thickness estimation are developed in a consistent framework. Finally, the result could be proofread in a cooperative environment. We validated and evaluated the approach using synthetic data and real images from clinical. The results showed that the system achieves a reasonable balance between fast speed and high accuracy.
{"title":"Rapid tracking of vascular tree in angiography images based on adaptive sampling","authors":"Xing Ming, Longjun He, Qian Liu","doi":"10.1109/ICMIPE.2013.6864556","DOIUrl":"https://doi.org/10.1109/ICMIPE.2013.6864556","url":null,"abstract":"Efficient assessment of vascular structures plays a significant role in many medical procedures. We present a practical approach to segmentation of vascular tree in angiography images. It is implemented in an interactive 3D visualization-assisted system and consists of the following main steps. First, angiography image is filtered to enhance vessels and eliminate irrelevant structures. Second, the centerline and thickness of the vessel are extracted utilizes a novel local tracking algorithm named adaptive sampling. The sampling starts from a single seed point and marches recursively forward along possible vessel continuations to capture whole tree-like structure, in which the branch detection and thickness estimation are developed in a consistent framework. Finally, the result could be proofread in a cooperative environment. We validated and evaluated the approach using synthetic data and real images from clinical. The results showed that the system achieves a reasonable balance between fast speed and high accuracy.","PeriodicalId":135461,"journal":{"name":"2013 IEEE International Conference on Medical Imaging Physics and Engineering","volume":"89 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116435810","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}
Pub Date : 2013-10-01DOI: 10.1109/ICMIPE.2013.6864499
Sun Dong, Shao Xiang-jun, L. Fusheng, Li Mintang, Xu Xinxi
A novel, standardized geometric model of the human upper respiratory tract was created by aligning and processing the computed tomography (CT) scans of upper respiratory airway of healthy subjects. Digital three-dimensional (3-D) geometric model of 3 single human upper respiratory airway were generated from the CT scans and a methodology was developed to scale, orient, and align the models, after which 2-D digital coronal cross-section slices were generated. With the use of an image processing algorithm, median cross-sectional geometries were created to match median physical parameters which retaining the unique geometric feature of human upper respiratory airway. From these idealized 2-D images and the original image-fusion model was created. Then, the statistical data of human upper respiratory airway was used to scale the model and to get the standardized model. Compared to the simplified model, the standardized model is more similar to the real human upper respiratory tract in the completeness of structural characteristics and the reality of geometry, the deviation degree of key dimension is only 0.16, and it possesses more application value in scientific research.
{"title":"Creation of standardized geometric model of the human upper respiratory airway","authors":"Sun Dong, Shao Xiang-jun, L. Fusheng, Li Mintang, Xu Xinxi","doi":"10.1109/ICMIPE.2013.6864499","DOIUrl":"https://doi.org/10.1109/ICMIPE.2013.6864499","url":null,"abstract":"A novel, standardized geometric model of the human upper respiratory tract was created by aligning and processing the computed tomography (CT) scans of upper respiratory airway of healthy subjects. Digital three-dimensional (3-D) geometric model of 3 single human upper respiratory airway were generated from the CT scans and a methodology was developed to scale, orient, and align the models, after which 2-D digital coronal cross-section slices were generated. With the use of an image processing algorithm, median cross-sectional geometries were created to match median physical parameters which retaining the unique geometric feature of human upper respiratory airway. From these idealized 2-D images and the original image-fusion model was created. Then, the statistical data of human upper respiratory airway was used to scale the model and to get the standardized model. Compared to the simplified model, the standardized model is more similar to the real human upper respiratory tract in the completeness of structural characteristics and the reality of geometry, the deviation degree of key dimension is only 0.16, and it possesses more application value in scientific research.","PeriodicalId":135461,"journal":{"name":"2013 IEEE International Conference on Medical Imaging Physics and Engineering","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134116967","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}
Pub Date : 2013-10-01DOI: 10.1109/ICMIPE.2013.6864491
Z. Shu-xu, Wang Rui-hao, Zhou Ling-hong, Yu Hui, Zhang Guo-quan, Qi Bing, L. Sheng-qu
BACKGROUND: Existing methods for quantification of lung ventilation require a tracer gas and specialized imaging such as single photon emission computed tomography (SPECT) or magnetic resonance imaging (MRI). Limitations of these methods include slow imaging speed, complex interpretation, and heavy burden on patients. OBJECTIVE: To assess 3D ventilation quantification based on 4D-CT and multi-resolution 3D B-spline deformable image registration (DIR). METHODS: All 4D-CT data sets were acquired with patients during quiet breathing. A 3D displacement vector field (DVF) of two different phase 4D-CT image pairs was calculated using 3D B-spline DIR algorithms, and converting to the Jacobian determinant. The axial grayscale images generated were colorized prior to fusion with the CT images and coronal and sagittal sections were reconstructed. The contours of the ventilation regions with different Jacobian values were delineated and their volumes were calculated. RESULTS: Based on 4D-CT images of patients and multi-resolution 3D B-spline DIR, 3D ventilation images can be easily generated and quantified. The maximum lung volume changes are significantly related to functional lung volumes at a level of P = 0.05 (bilateral). CONCLUSIONS: It is feasible to quantify the volume distribution of pulmonary ventilation based on 4D-CT images and 3D B-spline DIR. Key Words: Pulmonary Ventilation, Four-dimensional Computerized Tomography (4D-CT), Deformation Image Registration (DIR).
{"title":"3D pulmonary ventilation based on 4D-CT and Deformation Image Registration","authors":"Z. Shu-xu, Wang Rui-hao, Zhou Ling-hong, Yu Hui, Zhang Guo-quan, Qi Bing, L. Sheng-qu","doi":"10.1109/ICMIPE.2013.6864491","DOIUrl":"https://doi.org/10.1109/ICMIPE.2013.6864491","url":null,"abstract":"BACKGROUND: Existing methods for quantification of lung ventilation require a tracer gas and specialized imaging such as single photon emission computed tomography (SPECT) or magnetic resonance imaging (MRI). Limitations of these methods include slow imaging speed, complex interpretation, and heavy burden on patients. OBJECTIVE: To assess 3D ventilation quantification based on 4D-CT and multi-resolution 3D B-spline deformable image registration (DIR). METHODS: All 4D-CT data sets were acquired with patients during quiet breathing. A 3D displacement vector field (DVF) of two different phase 4D-CT image pairs was calculated using 3D B-spline DIR algorithms, and converting to the Jacobian determinant. The axial grayscale images generated were colorized prior to fusion with the CT images and coronal and sagittal sections were reconstructed. The contours of the ventilation regions with different Jacobian values were delineated and their volumes were calculated. RESULTS: Based on 4D-CT images of patients and multi-resolution 3D B-spline DIR, 3D ventilation images can be easily generated and quantified. The maximum lung volume changes are significantly related to functional lung volumes at a level of P = 0.05 (bilateral). CONCLUSIONS: It is feasible to quantify the volume distribution of pulmonary ventilation based on 4D-CT images and 3D B-spline DIR. Key Words: Pulmonary Ventilation, Four-dimensional Computerized Tomography (4D-CT), Deformation Image Registration (DIR).","PeriodicalId":135461,"journal":{"name":"2013 IEEE International Conference on Medical Imaging Physics and Engineering","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125753929","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}
Pub Date : 2013-10-01DOI: 10.1109/ICMIPE.2013.6864557
Wang Yang, Jin-Ren Liu
Medical image fusion is a kind of new technology including medical image treatment and diagnosis. It can be applied to a wide variety of medical fields such as clinic diagnosis and therapy, computer assistant diagnosis, long-distance medical treatment, radiation therapy and surgery plan design, etc. Digital image fusion is a comprehensive information of the multiple source images in order to obtain more accurate, more comprehensive and more reliable description for a particular region or target, so that it can facilitate the subsequent analysis and understanding of the image. This paper introduces the objective, content, methods and classification of medical image fusion. It also analyzes the difficulties, problems and future of medical image fusion.
{"title":"Research and development of medical image fusion","authors":"Wang Yang, Jin-Ren Liu","doi":"10.1109/ICMIPE.2013.6864557","DOIUrl":"https://doi.org/10.1109/ICMIPE.2013.6864557","url":null,"abstract":"Medical image fusion is a kind of new technology including medical image treatment and diagnosis. It can be applied to a wide variety of medical fields such as clinic diagnosis and therapy, computer assistant diagnosis, long-distance medical treatment, radiation therapy and surgery plan design, etc. Digital image fusion is a comprehensive information of the multiple source images in order to obtain more accurate, more comprehensive and more reliable description for a particular region or target, so that it can facilitate the subsequent analysis and understanding of the image. This paper introduces the objective, content, methods and classification of medical image fusion. It also analyzes the difficulties, problems and future of medical image fusion.","PeriodicalId":135461,"journal":{"name":"2013 IEEE International Conference on Medical Imaging Physics and Engineering","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130123951","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}
Pub Date : 2013-10-01DOI: 10.1109/ICMIPE.2013.6864514
Shouyu Zhang, Song Gao, X. Kang, S. Bao
Since the birth of diffusion tensor imaging (DTI), diffusion characteristic has become a powerful tool to probe the internal structure of the subject. The diffusion anisotropy indices (DAIs) are parameters derived from DTI data which describe the morphological characteristics of diffusion tensor within specific range. It is of great importance to select a proper DAI for the analysis and interpretation of DTI data. In this work, the diffusion characteristic in human visual cortex is analysed with three DAIs: the commonly used fractional anisotropy (FA), ellipsoidal geometric ratio (EAR) proposed lately and ellipsoidal geometric ratio (EGR) that we proposed. The retinotopic mapping and surface-based analysis methods were applied to increase the power and precision studying longitudinal DAI changes in different visual fields (V1, V2, V3 et al). All three DAIs show the similar trend in visual fields, however, EGR and EAR both have higher magnitude and better contrast than FA. In addition, since EGR makes full use of the ellipsoidal volume information, its application result shows a certain improvement compared with EAR.
{"title":"Diffusion characteristic analysis in human visual cortex","authors":"Shouyu Zhang, Song Gao, X. Kang, S. Bao","doi":"10.1109/ICMIPE.2013.6864514","DOIUrl":"https://doi.org/10.1109/ICMIPE.2013.6864514","url":null,"abstract":"Since the birth of diffusion tensor imaging (DTI), diffusion characteristic has become a powerful tool to probe the internal structure of the subject. The diffusion anisotropy indices (DAIs) are parameters derived from DTI data which describe the morphological characteristics of diffusion tensor within specific range. It is of great importance to select a proper DAI for the analysis and interpretation of DTI data. In this work, the diffusion characteristic in human visual cortex is analysed with three DAIs: the commonly used fractional anisotropy (FA), ellipsoidal geometric ratio (EAR) proposed lately and ellipsoidal geometric ratio (EGR) that we proposed. The retinotopic mapping and surface-based analysis methods were applied to increase the power and precision studying longitudinal DAI changes in different visual fields (V1, V2, V3 et al). All three DAIs show the similar trend in visual fields, however, EGR and EAR both have higher magnitude and better contrast than FA. In addition, since EGR makes full use of the ellipsoidal volume information, its application result shows a certain improvement compared with EAR.","PeriodicalId":135461,"journal":{"name":"2013 IEEE International Conference on Medical Imaging Physics and Engineering","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117051906","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}
Pub Date : 2013-10-01DOI: 10.1109/ICMIPE.2013.6864529
Yaonan Zhang, Xian Li, Sai Li, Hongliang Li, Hairong Zheng
In Ultrasound elastography, the decorrelation effect of the tissue under slightly amount of compression (less than 1%) is mainly caused by nonlinear tissue deformation, therefore the image noise caused by decorrelation is system-independent, which also becomes the major constraints for strain estimation and imaging. In this paper, one-dimensional adaptive extension method in time domain and amplitude correction method are proposed to improve signal coincidence degree, thus we get the maximum cross-correlation coefficient and finally improve the accuracy of time delay estimation and the quality of elastography.
{"title":"An accurate method of ultrasonic strain estimation under slight tissue compression","authors":"Yaonan Zhang, Xian Li, Sai Li, Hongliang Li, Hairong Zheng","doi":"10.1109/ICMIPE.2013.6864529","DOIUrl":"https://doi.org/10.1109/ICMIPE.2013.6864529","url":null,"abstract":"In Ultrasound elastography, the decorrelation effect of the tissue under slightly amount of compression (less than 1%) is mainly caused by nonlinear tissue deformation, therefore the image noise caused by decorrelation is system-independent, which also becomes the major constraints for strain estimation and imaging. In this paper, one-dimensional adaptive extension method in time domain and amplitude correction method are proposed to improve signal coincidence degree, thus we get the maximum cross-correlation coefficient and finally improve the accuracy of time delay estimation and the quality of elastography.","PeriodicalId":135461,"journal":{"name":"2013 IEEE International Conference on Medical Imaging Physics and Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123002819","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}
Pub Date : 2013-10-01DOI: 10.1109/ICMIPE.2013.6864496
Y. Lei, Yan Zhang
An accurate two-dimensional-three-dimensional (2D-3D) image registration method is introduced in this paper, which is used in image-guided surgery to detect and correct patient movement during image-guided intervention treatment. In this paper, we decompose a 3D rigid transformation in the 3D patient coordinate into in-plane transformations and out-of-plane rotations in two orthogonal 2D projections, using approximate geometric relationship and the results in the two projections are then combined and converted to a 3D rigid transformation by 2D-3D geometric transformation. In order to ensure accuracy, we propose that using mutual information based on partial volume interpolation as a similarity measure to align Digitally Reconstructed Radiographs(DRRs) from original 3D CT volume and x-ray images. In the refined stage, we use expanded Powell method to search for the refined parameters. Our experiments show that it is feasible of the assessed 2D-3D registration algorithm, since it achieves sub-millimeter accuracy, when modified mutual information and expanded Powell search method are used.
{"title":"An improved 2D-3D medical image registration algorithm based on modified mutual information and expanded Powell method","authors":"Y. Lei, Yan Zhang","doi":"10.1109/ICMIPE.2013.6864496","DOIUrl":"https://doi.org/10.1109/ICMIPE.2013.6864496","url":null,"abstract":"An accurate two-dimensional-three-dimensional (2D-3D) image registration method is introduced in this paper, which is used in image-guided surgery to detect and correct patient movement during image-guided intervention treatment. In this paper, we decompose a 3D rigid transformation in the 3D patient coordinate into in-plane transformations and out-of-plane rotations in two orthogonal 2D projections, using approximate geometric relationship and the results in the two projections are then combined and converted to a 3D rigid transformation by 2D-3D geometric transformation. In order to ensure accuracy, we propose that using mutual information based on partial volume interpolation as a similarity measure to align Digitally Reconstructed Radiographs(DRRs) from original 3D CT volume and x-ray images. In the refined stage, we use expanded Powell method to search for the refined parameters. Our experiments show that it is feasible of the assessed 2D-3D registration algorithm, since it achieves sub-millimeter accuracy, when modified mutual information and expanded Powell search method are used.","PeriodicalId":135461,"journal":{"name":"2013 IEEE International Conference on Medical Imaging Physics and Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121219313","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}
Pub Date : 2013-10-01DOI: 10.1109/ICMIPE.2013.6864523
Xu Dai, J. Ronsky
Osteoarthritis (OA) is a degenerative joint disease that leads to the articular cartilage (AC) degeneration and joint function loss. Early stage OA is primarily associated with proteoglycan (PG) loss and collagen structure changes. The MR T2 imaging is a promising non-invasive diagnostic tool that has shown the potential to reflect changes in the biochemical composition of cartilage with early OA. T2 relaxation times give a quantitative measure of the molecular interactions occurring within the imaged cartilage tissues. It can represent cartilage tissue biochemical character that can be quantified with the help of specific imaging strategies. The goal of this study was to apply Levenberg-Marquardt curve fitting algorithm for T2 mapping quantification and T2 relaxation time calculation to study T2 relaxation characters based on quantitative MR T2 imaging of the tibiofemoral condyle cartilage. The MR T2 images of a healthy male volunteer's right knee were generated by a 3T MRI scanner using a spin echo multislice multiecho (MSME) Carr-Purcell Meiboom-Gill (CPMG) sequence. The medial and lateral tibiofemoral condyle cartilage was further subdivided into the regions of interest (ROIs) for identifying variation in T2 values. T2 relaxation times mean and standard deviation of ROIs were calculated using Levenberg-Marquardt curve fitting algorithm with correction and without correction. The results show that the Levenberg-Marquardt curve fitting algorithm was feasible for T2 relaxation time calculation of tibiofemoral cartilage, the CPMG sequence was sensitive to cartilage tissue imaging, and T2 parameter can be used for the characterization of articular cartilage tissue.
{"title":"The study of knee tibiofemoral condyle cartilage relaxation characters based on quantitative MR T2 imaging","authors":"Xu Dai, J. Ronsky","doi":"10.1109/ICMIPE.2013.6864523","DOIUrl":"https://doi.org/10.1109/ICMIPE.2013.6864523","url":null,"abstract":"Osteoarthritis (OA) is a degenerative joint disease that leads to the articular cartilage (AC) degeneration and joint function loss. Early stage OA is primarily associated with proteoglycan (PG) loss and collagen structure changes. The MR T2 imaging is a promising non-invasive diagnostic tool that has shown the potential to reflect changes in the biochemical composition of cartilage with early OA. T2 relaxation times give a quantitative measure of the molecular interactions occurring within the imaged cartilage tissues. It can represent cartilage tissue biochemical character that can be quantified with the help of specific imaging strategies. The goal of this study was to apply Levenberg-Marquardt curve fitting algorithm for T2 mapping quantification and T2 relaxation time calculation to study T2 relaxation characters based on quantitative MR T2 imaging of the tibiofemoral condyle cartilage. The MR T2 images of a healthy male volunteer's right knee were generated by a 3T MRI scanner using a spin echo multislice multiecho (MSME) Carr-Purcell Meiboom-Gill (CPMG) sequence. The medial and lateral tibiofemoral condyle cartilage was further subdivided into the regions of interest (ROIs) for identifying variation in T2 values. T2 relaxation times mean and standard deviation of ROIs were calculated using Levenberg-Marquardt curve fitting algorithm with correction and without correction. The results show that the Levenberg-Marquardt curve fitting algorithm was feasible for T2 relaxation time calculation of tibiofemoral cartilage, the CPMG sequence was sensitive to cartilage tissue imaging, and T2 parameter can be used for the characterization of articular cartilage tissue.","PeriodicalId":135461,"journal":{"name":"2013 IEEE International Conference on Medical Imaging Physics and Engineering","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130360656","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}
Pub Date : 2013-10-01DOI: 10.1109/ICMIPE.2013.6864535
Kai Zhu, Guijie Li, Xin Zhao
To explore the enhancement effect of contrast media on primary cancer of cheek carcinoma by local injection. The carcinoma mice models were established, then self-made contrast media was administered into the primary cheek carcinoma, and harmonic mode imaging was performed to observe the enhancement of primary lesions. The echo intensity (EI) was compared, after contrast-enhanced ultrasound (CEUS) imaging, the EI of primary cancer was increased. After injection of self-made contrast media via the primary lesion, it can obviously enhance the effect of ultrasonography on cheek carcinoma.
{"title":"Ultrasound microbubbles in diagnosis of buccal carcinoma","authors":"Kai Zhu, Guijie Li, Xin Zhao","doi":"10.1109/ICMIPE.2013.6864535","DOIUrl":"https://doi.org/10.1109/ICMIPE.2013.6864535","url":null,"abstract":"To explore the enhancement effect of contrast media on primary cancer of cheek carcinoma by local injection. The carcinoma mice models were established, then self-made contrast media was administered into the primary cheek carcinoma, and harmonic mode imaging was performed to observe the enhancement of primary lesions. The echo intensity (EI) was compared, after contrast-enhanced ultrasound (CEUS) imaging, the EI of primary cancer was increased. After injection of self-made contrast media via the primary lesion, it can obviously enhance the effect of ultrasonography on cheek carcinoma.","PeriodicalId":135461,"journal":{"name":"2013 IEEE International Conference on Medical Imaging Physics and Engineering","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124504957","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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