{"title":"基于TMS320C6713 DSK的DSP环境下脑肿瘤检测的应用","authors":"Boucif Beddad, K. Hachemi","doi":"10.1109/TSP.2017.8076057","DOIUrl":null,"url":null,"abstract":"Medical image processing continues to enable the biomedical technology revolution that we are experiencing today. In this brief paper the main purpose of the project is to carry out a new cooperative approach for brain tumor segmentation and feature extraction from Magnetic Resonance Imaging with the good accuracy. The basic process involves is to use the notion of the modified Fuzzy C-Means which incorporates the spatial information and also in order to improve the segmentation and to get a better estimation of the final clusters centers. Then FCM_S results are considered as an initialization of the active edge for the Level sets algorithm. Digital Signal Processor chip of Texas instruments TMS320C6713 DSK with the Code Composer Studio and Matlab Simulink Blocksets are used for implementing this proposed work. The performance is measured by including some various optimization techniques and all results are shown using C67613 Graphical User Interface. The Development Starter Kit is also studied for available resource and their appropriate usage.","PeriodicalId":256818,"journal":{"name":"2017 40th International Conference on Telecommunications and Signal Processing (TSP)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Application of brain tumor detection on DSP environment using TMS320C6713 DSK\",\"authors\":\"Boucif Beddad, K. Hachemi\",\"doi\":\"10.1109/TSP.2017.8076057\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Medical image processing continues to enable the biomedical technology revolution that we are experiencing today. In this brief paper the main purpose of the project is to carry out a new cooperative approach for brain tumor segmentation and feature extraction from Magnetic Resonance Imaging with the good accuracy. The basic process involves is to use the notion of the modified Fuzzy C-Means which incorporates the spatial information and also in order to improve the segmentation and to get a better estimation of the final clusters centers. Then FCM_S results are considered as an initialization of the active edge for the Level sets algorithm. Digital Signal Processor chip of Texas instruments TMS320C6713 DSK with the Code Composer Studio and Matlab Simulink Blocksets are used for implementing this proposed work. The performance is measured by including some various optimization techniques and all results are shown using C67613 Graphical User Interface. The Development Starter Kit is also studied for available resource and their appropriate usage.\",\"PeriodicalId\":256818,\"journal\":{\"name\":\"2017 40th International Conference on Telecommunications and Signal Processing (TSP)\",\"volume\":\"9 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 40th International Conference on Telecommunications and Signal Processing (TSP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/TSP.2017.8076057\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 40th International Conference on Telecommunications and Signal Processing (TSP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TSP.2017.8076057","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Application of brain tumor detection on DSP environment using TMS320C6713 DSK
Medical image processing continues to enable the biomedical technology revolution that we are experiencing today. In this brief paper the main purpose of the project is to carry out a new cooperative approach for brain tumor segmentation and feature extraction from Magnetic Resonance Imaging with the good accuracy. The basic process involves is to use the notion of the modified Fuzzy C-Means which incorporates the spatial information and also in order to improve the segmentation and to get a better estimation of the final clusters centers. Then FCM_S results are considered as an initialization of the active edge for the Level sets algorithm. Digital Signal Processor chip of Texas instruments TMS320C6713 DSK with the Code Composer Studio and Matlab Simulink Blocksets are used for implementing this proposed work. The performance is measured by including some various optimization techniques and all results are shown using C67613 Graphical User Interface. The Development Starter Kit is also studied for available resource and their appropriate usage.