Pub Date : 2013-10-01DOI: 10.1109/ICMIPE.2013.6864544
Jian-hua Gao, F. Zhou, Bo Liu
In order to provide prostate biopsy operators with information from pre-operative MR images, MR images must be transformed accurately to the Transrectal Ultrasound (TRUS) real-time images. In our work, we used the well-known Robust Points Matching (RPM) algorithm to find the corresponding point pairs from the prostate contours of MR and TRUS and the thin plate splines (TPS) to transform MRI to TRUS images elastically. Compared with choosing landmarks based on key structures adopted by Nasr Makni[11], we find generating point sets by down-sampling the manual delineated contours in two modality images is much more robust and easier, as it depends little on the experience of operators as well as the quality of clinical ultrasound imaging. Using data acquired from 5 patients, the mean DSC (Disc Similarity Coefficient) we get after performing RPM-TPS registration was 79.43%, compared to the 60.20% got by the manual rigid registration.
{"title":"Elastic image registration of MR/TRUS for targeted prostate biopsy","authors":"Jian-hua Gao, F. Zhou, Bo Liu","doi":"10.1109/ICMIPE.2013.6864544","DOIUrl":"https://doi.org/10.1109/ICMIPE.2013.6864544","url":null,"abstract":"In order to provide prostate biopsy operators with information from pre-operative MR images, MR images must be transformed accurately to the Transrectal Ultrasound (TRUS) real-time images. In our work, we used the well-known Robust Points Matching (RPM) algorithm to find the corresponding point pairs from the prostate contours of MR and TRUS and the thin plate splines (TPS) to transform MRI to TRUS images elastically. Compared with choosing landmarks based on key structures adopted by Nasr Makni[11], we find generating point sets by down-sampling the manual delineated contours in two modality images is much more robust and easier, as it depends little on the experience of operators as well as the quality of clinical ultrasound imaging. Using data acquired from 5 patients, the mean DSC (Disc Similarity Coefficient) we get after performing RPM-TPS registration was 79.43%, compared to the 60.20% got by the manual rigid registration.","PeriodicalId":135461,"journal":{"name":"2013 IEEE International Conference on Medical Imaging Physics and Engineering","volume":"392 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":"123516957","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.2013.6864542
Hannong Lu, Zheng Cuan, F. Zhou, Bo Liu
Post-implant dosimetric evaluation is a key procedure of brachytherapy. The way of traditional manual localizing seed is lack of efficiency. Therefore, Automatic seed detection method is needed to efficiently and accurately calculate the centroid and orientation. There are some shape differences among seeds, caused by imaging features. Single seed may be presented on more than one slice and seeds locating closely may appear connected. This paper proposed an automatic three-dimensional detection method of seeds on CT images. Firstly, the areas possibly containing seeds are got by binary threshold on each CT slice and the related geometric information was recorded. Then, the larger areas containing more than one seed are segmented by watershed algorithm. According to the max seed volume rule and straight line rule, the areas are connected into the complete seed volume and the weighted centroid and orientation are calculated. The statistical analysis demonstrates that the rate of seed detection can achieve 97% and has a high applicability of post-implant dosimetric verification.
{"title":"An automatic 3D detection method of seeds on CT images","authors":"Hannong Lu, Zheng Cuan, F. Zhou, Bo Liu","doi":"10.1109/ICMIPE.2013.6864542","DOIUrl":"https://doi.org/10.1109/ICMIPE.2013.6864542","url":null,"abstract":"Post-implant dosimetric evaluation is a key procedure of brachytherapy. The way of traditional manual localizing seed is lack of efficiency. Therefore, Automatic seed detection method is needed to efficiently and accurately calculate the centroid and orientation. There are some shape differences among seeds, caused by imaging features. Single seed may be presented on more than one slice and seeds locating closely may appear connected. This paper proposed an automatic three-dimensional detection method of seeds on CT images. Firstly, the areas possibly containing seeds are got by binary threshold on each CT slice and the related geometric information was recorded. Then, the larger areas containing more than one seed are segmented by watershed algorithm. According to the max seed volume rule and straight line rule, the areas are connected into the complete seed volume and the weighted centroid and orientation are calculated. The statistical analysis demonstrates that the rate of seed detection can achieve 97% and has a high applicability of post-implant dosimetric verification.","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":"125826745","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.2013.6864554
Jing Xiang-yu, Rong Jian, Zhong Xiaochun, Gao Yi, Huang Lin, Li Tingting
This paper presents preliminary in vitro experimental studies in imaging of the same joint using laser-based photoacoustic imaging and microwave-based thermoacoustic imaging. In this pilot study, the experiments were conducted on the same chicken claw joint in vitro, and a delay-and-sum algorithm was used to reconstruct the two-dimensional (2D) photoacoustic and thermoacoustic images. In the future, integrating the two imaging modalities into a system, which combines the merits of two imaging modalities, has potential to provide an effective approach of tissue structure and functional images to study the architectures, physiological and pathological properties and metabolisms of joint tissues.
{"title":"Photoacoustic and thermoacoustic imaging application in joint imaging","authors":"Jing Xiang-yu, Rong Jian, Zhong Xiaochun, Gao Yi, Huang Lin, Li Tingting","doi":"10.1109/ICMIPE.2013.6864554","DOIUrl":"https://doi.org/10.1109/ICMIPE.2013.6864554","url":null,"abstract":"This paper presents preliminary in vitro experimental studies in imaging of the same joint using laser-based photoacoustic imaging and microwave-based thermoacoustic imaging. In this pilot study, the experiments were conducted on the same chicken claw joint in vitro, and a delay-and-sum algorithm was used to reconstruct the two-dimensional (2D) photoacoustic and thermoacoustic images. In the future, integrating the two imaging modalities into a system, which combines the merits of two imaging modalities, has potential to provide an effective approach of tissue structure and functional images to study the architectures, physiological and pathological properties and metabolisms of joint tissues.","PeriodicalId":135461,"journal":{"name":"2013 IEEE International Conference on Medical Imaging Physics and Engineering","volume":"28 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":"129441717","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.2013.6864538
Yang Xuan, Xu Wang, Cheng'an Liu, Dan Yang
This paper is focus on the forward problem of 3-D magnetic induction tomography. Finite element method (FEM) has been used to analyse and calculate the problem. The analysis process performed by ANSYS software. First, we establish a 3-D solid model of magnetic imaging system. Then we mesh it to FE model by meshing tools. Using, the A̅, A̅ - φ method to indicate governing equation for reducing calculated amount. A̅ is magnetic vector potential, and A̅ is electric scalar potential. The discrete equations are Established by Galekin finite element discretization format, and solve them by using sparse matrix direct solution. In order to study the influence on the results of meshing density, this paper uses 3 different meshing methods for comparing and analyzing results. Simulation results show that the meshing density affects the results in different ways. Although the absolute values of SCR are changed, but the linear relation between SCR and conductivity is good.
{"title":"A FEM method for magnetic induction tomography forward problem","authors":"Yang Xuan, Xu Wang, Cheng'an Liu, Dan Yang","doi":"10.1109/ICMIPE.2013.6864538","DOIUrl":"https://doi.org/10.1109/ICMIPE.2013.6864538","url":null,"abstract":"This paper is focus on the forward problem of 3-D magnetic induction tomography. Finite element method (FEM) has been used to analyse and calculate the problem. The analysis process performed by ANSYS software. First, we establish a 3-D solid model of magnetic imaging system. Then we mesh it to FE model by meshing tools. Using, the A̅, A̅ - φ method to indicate governing equation for reducing calculated amount. A̅ is magnetic vector potential, and A̅ is electric scalar potential. The discrete equations are Established by Galekin finite element discretization format, and solve them by using sparse matrix direct solution. In order to study the influence on the results of meshing density, this paper uses 3 different meshing methods for comparing and analyzing results. Simulation results show that the meshing density affects the results in different ways. Although the absolute values of SCR are changed, but the linear relation between SCR and conductivity is good.","PeriodicalId":135461,"journal":{"name":"2013 IEEE International Conference on Medical Imaging Physics and Engineering","volume":"7 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":"128547894","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.2013.6864541
Sun Mengmeng, W. Shuicai
To display and process images in different DICOM formats, this article introduces a new method of integrating ITK, VTK and QT to process the images in DICOM format, and a software was designed based on the three tools. The results indicate that this software can read and display DICOM images with different suffixes and can process medical images simply.
{"title":"A software development of DICOM image processing based on QT, VTK and ITK","authors":"Sun Mengmeng, W. Shuicai","doi":"10.1109/ICMIPE.2013.6864541","DOIUrl":"https://doi.org/10.1109/ICMIPE.2013.6864541","url":null,"abstract":"To display and process images in different DICOM formats, this article introduces a new method of integrating ITK, VTK and QT to process the images in DICOM format, and a software was designed based on the three tools. The results indicate that this software can read and display DICOM images with different suffixes and can process medical images simply.","PeriodicalId":135461,"journal":{"name":"2013 IEEE International Conference on Medical Imaging Physics and Engineering","volume":"63 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":"130929734","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.2013.6864558
Jihong Liu, Na Zhao, Runnan He
Objective: To design and build up a computer-aided color matching system for porcelain tooth, which could offer dentists an objective suggestion for selecting the color of the patient's tooth. Methods: The color matching system is mainly based on image analyzing and processing techniques and pattern recognition methods. This system uses HSI color space to compare and calculate colors. The system consists of five parts, which are image acquisition facility, image processing part, tooth color classification module, color mixture module and a template library. This system uses image analyzing technology to find out tooth image's color feature and then look it up in the template library to get the standard term of this tooth's color using pattern recognition methods. Results and discussions: Firstly, we use the minimum distance classifier and do two experiments with three tooth models of the identifier 0M1, 3M2 and 5M1. In the first experiment, we take 20 pictures as samples for each tooth model, setting the first 5 pictures as training samples and the last 5 pictures as testing samples. The recognition rate is 66.7%. In the second experiment, we use the former 10 pictures of each tooth model as training samples and the other 10 pictures as testing samples. The recognition is 90%. In addition, we use KNN classifier to test the above test datasets, but the recognition rates are obviously lower than those obtained by the minimum distance classifier. Conclusions: The tools and processing platform used in this experiment are simple and efficient. The recognition rate of this color matching system is good and accepted.
{"title":"Study of color matching system for porcelain teeth","authors":"Jihong Liu, Na Zhao, Runnan He","doi":"10.1109/ICMIPE.2013.6864558","DOIUrl":"https://doi.org/10.1109/ICMIPE.2013.6864558","url":null,"abstract":"Objective: To design and build up a computer-aided color matching system for porcelain tooth, which could offer dentists an objective suggestion for selecting the color of the patient's tooth. Methods: The color matching system is mainly based on image analyzing and processing techniques and pattern recognition methods. This system uses HSI color space to compare and calculate colors. The system consists of five parts, which are image acquisition facility, image processing part, tooth color classification module, color mixture module and a template library. This system uses image analyzing technology to find out tooth image's color feature and then look it up in the template library to get the standard term of this tooth's color using pattern recognition methods. Results and discussions: Firstly, we use the minimum distance classifier and do two experiments with three tooth models of the identifier 0M1, 3M2 and 5M1. In the first experiment, we take 20 pictures as samples for each tooth model, setting the first 5 pictures as training samples and the last 5 pictures as testing samples. The recognition rate is 66.7%. In the second experiment, we use the former 10 pictures of each tooth model as training samples and the other 10 pictures as testing samples. The recognition is 90%. In addition, we use KNN classifier to test the above test datasets, but the recognition rates are obviously lower than those obtained by the minimum distance classifier. Conclusions: The tools and processing platform used in this experiment are simple and efficient. The recognition rate of this color matching system is good and accepted.","PeriodicalId":135461,"journal":{"name":"2013 IEEE International Conference on Medical Imaging Physics and Engineering","volume":"111 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":"122348329","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.2013.6864546
Yi Liu, Xiaoming Wu, Mingku Feng
In the paper, the EEG features under electrical stimulation is studied. After analysis the data that collected in experiment by the method of wavelet entropy and complexity, we found that electrical stimulation can obviously change the complexity of brain signals, and the wavelet energy entropy of its brain signals have notable changes as well. According the result of coherence estimation, it is found that electrical stimulation has notable effects to brain. It provides a new method to study the influence to brain by electrical simulation that used in rehabilitation of hemiplegic patients with stroke.
{"title":"Extraction and analysis of EEG features under electric stimulation","authors":"Yi Liu, Xiaoming Wu, Mingku Feng","doi":"10.1109/ICMIPE.2013.6864546","DOIUrl":"https://doi.org/10.1109/ICMIPE.2013.6864546","url":null,"abstract":"In the paper, the EEG features under electrical stimulation is studied. After analysis the data that collected in experiment by the method of wavelet entropy and complexity, we found that electrical stimulation can obviously change the complexity of brain signals, and the wavelet energy entropy of its brain signals have notable changes as well. According the result of coherence estimation, it is found that electrical stimulation has notable effects to brain. It provides a new method to study the influence to brain by electrical simulation that used in rehabilitation of hemiplegic patients with stroke.","PeriodicalId":135461,"journal":{"name":"2013 IEEE International Conference on Medical Imaging Physics and Engineering","volume":"72 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":"121133583","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.2013.6864528
Yaonan Zhang, Qian Song, Chuanshen Chen, X. Meng
Due to the unique characteristics of right ventricle, such as volatile, thin wall, unobvious boundary, multi-Atlas algorithm is appropriate for its segmentation. However, most of the existing Atlas select methods are based on choosing Atlas after registering, while the registering is time consuming and reduce the segmentation performance. For this reasons, we introduce a new Multi-Atlas selection method based on affinity propagation clustering algorithm. Firstly, see all Atlas images as a series of data points, clustering them through message propagation. Secondly, register all the clustering centre images to target image, getting deformation markers results by STAPLE label fusion. Finally, sort all the fusion results by dice similarity coefficient. Register and fusion the clustering center images which own the biggest dice similarity coefficient. Furthermore, repeating the process above until get accurate segmentation. Experiment results show that the proposed method can segment right ventricle effectively. Compared to the traditional selection ways, segmentation accuracy has been greatly improved through this method.
{"title":"Accurate segmentation for right ventricles based on affinity propagation clustering and multi-Atlas selection","authors":"Yaonan Zhang, Qian Song, Chuanshen Chen, X. Meng","doi":"10.1109/ICMIPE.2013.6864528","DOIUrl":"https://doi.org/10.1109/ICMIPE.2013.6864528","url":null,"abstract":"Due to the unique characteristics of right ventricle, such as volatile, thin wall, unobvious boundary, multi-Atlas algorithm is appropriate for its segmentation. However, most of the existing Atlas select methods are based on choosing Atlas after registering, while the registering is time consuming and reduce the segmentation performance. For this reasons, we introduce a new Multi-Atlas selection method based on affinity propagation clustering algorithm. Firstly, see all Atlas images as a series of data points, clustering them through message propagation. Secondly, register all the clustering centre images to target image, getting deformation markers results by STAPLE label fusion. Finally, sort all the fusion results by dice similarity coefficient. Register and fusion the clustering center images which own the biggest dice similarity coefficient. Furthermore, repeating the process above until get accurate segmentation. Experiment results show that the proposed method can segment right ventricle effectively. Compared to the traditional selection ways, segmentation accuracy has been greatly improved through this method.","PeriodicalId":135461,"journal":{"name":"2013 IEEE International Conference on Medical Imaging Physics and Engineering","volume":"10 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":"121828662","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 evaluated the performance of two-dimensional (2D) and 3D texture features from CT images on pulmonary nodules diagnosis using the large database LIDC-IDRI. Total of 905 nodules (422 malignant and 483 benign) with certain expert observer ratings of malignancy were extracted from the database based on the radiologists' painting boundaries. Feature analysis on the extracted nodules was not only based on the popular texture analysis method, e.g., the 2D Haralick texture feature model, we also explored a 3D Haralick feature model with variable directions in space. The relationships of more neighbour voxels on more directions were included for texture feature analysis. The well-established Support Vector Machine (SVM) classifier was used for the malignancy classification based on the 2D and 3D Haralick texture features. Half of the benign and malignant nodules were extracted randomly for training, and the left half nodules for testing. This operation was implemented for 100 iterations. Then the 100 classification results were shown based on the area under the curve (AUC) of the Receiver Operating Characteristics (ROC). The distinguishing results on the nodule malignancy based on the 3D Haralick texture features (Az = 0.9441) is noticeably more consistent with the expert observer ratings than that on the 2D features (Az = 0.9372).
{"title":"A texture feature analysis for diagnosis of pulmonary nodules using LIDC-IDRI database","authors":"Fangfang Han, Guopeng Zhang, Huafeng Wang, Bowen Song, Hongbing Lu, Dazhe Zhao, Hong Zhao, Zhengrong Liang","doi":"10.1109/ICMIPE.2013.6864494","DOIUrl":"https://doi.org/10.1109/ICMIPE.2013.6864494","url":null,"abstract":"This paper evaluated the performance of two-dimensional (2D) and 3D texture features from CT images on pulmonary nodules diagnosis using the large database LIDC-IDRI. Total of 905 nodules (422 malignant and 483 benign) with certain expert observer ratings of malignancy were extracted from the database based on the radiologists' painting boundaries. Feature analysis on the extracted nodules was not only based on the popular texture analysis method, e.g., the 2D Haralick texture feature model, we also explored a 3D Haralick feature model with variable directions in space. The relationships of more neighbour voxels on more directions were included for texture feature analysis. The well-established Support Vector Machine (SVM) classifier was used for the malignancy classification based on the 2D and 3D Haralick texture features. Half of the benign and malignant nodules were extracted randomly for training, and the left half nodules for testing. This operation was implemented for 100 iterations. Then the 100 classification results were shown based on the area under the curve (AUC) of the Receiver Operating Characteristics (ROC). The distinguishing results on the nodule malignancy based on the 3D Haralick texture features (Az = 0.9441) is noticeably more consistent with the expert observer ratings than that on the 2D features (Az = 0.9372).","PeriodicalId":135461,"journal":{"name":"2013 IEEE International Conference on Medical Imaging Physics and Engineering","volume":" 15","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114051233","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.2013.6864548
Ping Tao, Weifeng Liu, Xiaoying Tang
In this paper an EHG signal acquisition and processing system has been designed, it adopted TMS320DM6446 chip to be the master controller and a new mechanism of communication between ARM and DSP is also designed for TMS320DM6446. The EHG signal was directly collected by ADS1298 chip, after preprocessing and wavelet analysis, the signal was compared with the normal EHG signal from the pregnant women who childbirth smooth, the result can predict if the pregnant is in danger of premature and dystocia.
{"title":"Human surface EHG acquisition and analysis system based on DM6446","authors":"Ping Tao, Weifeng Liu, Xiaoying Tang","doi":"10.1109/ICMIPE.2013.6864548","DOIUrl":"https://doi.org/10.1109/ICMIPE.2013.6864548","url":null,"abstract":"In this paper an EHG signal acquisition and processing system has been designed, it adopted TMS320DM6446 chip to be the master controller and a new mechanism of communication between ARM and DSP is also designed for TMS320DM6446. The EHG signal was directly collected by ADS1298 chip, after preprocessing and wavelet analysis, the signal was compared with the normal EHG signal from the pregnant women who childbirth smooth, the result can predict if the pregnant is in danger of premature and dystocia.","PeriodicalId":135461,"journal":{"name":"2013 IEEE International Conference on Medical Imaging Physics and Engineering","volume":"378 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":"122508725","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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