A. Fadeev, N. Eltonsy, G. Tourassi, Adel Said Elmaghraby
{"title":"用于三维体重建的快速变形插值模型质量评估","authors":"A. Fadeev, N. Eltonsy, G. Tourassi, Adel Said Elmaghraby","doi":"10.1109/ISSPIT.2005.1577201","DOIUrl":null,"url":null,"abstract":"The purpose of this study is to evaluate a 3D volume reconstruction model for volume rendering. The model is conducted using brain MRI data of Visible Human Project. Particularly MRI T1 data were used. The quality of the developed model is compared with linear interpolation technique. By applying our morphing technique recursively, taking progressively smaller subregions within a region, a high quality and accuracy interpolation is obtained. The presented algorithm is robust and has 20 adjustable parameters for use with different modalities. The main advantages of this morphing algorithm are: 1) applicability to general configurations of planes in 3D space, 2) automated behavior, 3) applicability to CT scans with no changes in the algorithm and software. Subsequently, to visualize data, a specialized volume rendering card (TeraRecon VolumePro 1000) was used. To represent data in 3D space, special software was developed to convert interpolated CT slices to 3D objects compatible with the VolumePro card. Quantitative and visual comparison between the proposed model and linear interpolation clearly demonstrates the superiority of the proposed model. Evaluation is performed by removing slices from the original stack of 2D images and using them as reference for error comparison among alternative approaches. Error analysis using average Mean Square and Absolute error clearly demonstrates improved performance","PeriodicalId":421826,"journal":{"name":"Proceedings of the Fifth IEEE International Symposium on Signal Processing and Information Technology, 2005.","volume":"54 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Quality evaluation of fast morphing interpolation model for 3D volume reconstruction\",\"authors\":\"A. Fadeev, N. Eltonsy, G. Tourassi, Adel Said Elmaghraby\",\"doi\":\"10.1109/ISSPIT.2005.1577201\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The purpose of this study is to evaluate a 3D volume reconstruction model for volume rendering. The model is conducted using brain MRI data of Visible Human Project. Particularly MRI T1 data were used. The quality of the developed model is compared with linear interpolation technique. By applying our morphing technique recursively, taking progressively smaller subregions within a region, a high quality and accuracy interpolation is obtained. The presented algorithm is robust and has 20 adjustable parameters for use with different modalities. The main advantages of this morphing algorithm are: 1) applicability to general configurations of planes in 3D space, 2) automated behavior, 3) applicability to CT scans with no changes in the algorithm and software. Subsequently, to visualize data, a specialized volume rendering card (TeraRecon VolumePro 1000) was used. To represent data in 3D space, special software was developed to convert interpolated CT slices to 3D objects compatible with the VolumePro card. Quantitative and visual comparison between the proposed model and linear interpolation clearly demonstrates the superiority of the proposed model. Evaluation is performed by removing slices from the original stack of 2D images and using them as reference for error comparison among alternative approaches. Error analysis using average Mean Square and Absolute error clearly demonstrates improved performance\",\"PeriodicalId\":421826,\"journal\":{\"name\":\"Proceedings of the Fifth IEEE International Symposium on Signal Processing and Information Technology, 2005.\",\"volume\":\"54 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-12-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Fifth IEEE International Symposium on Signal Processing and Information Technology, 2005.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISSPIT.2005.1577201\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Fifth IEEE International Symposium on Signal Processing and Information Technology, 2005.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISSPIT.2005.1577201","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Quality evaluation of fast morphing interpolation model for 3D volume reconstruction
The purpose of this study is to evaluate a 3D volume reconstruction model for volume rendering. The model is conducted using brain MRI data of Visible Human Project. Particularly MRI T1 data were used. The quality of the developed model is compared with linear interpolation technique. By applying our morphing technique recursively, taking progressively smaller subregions within a region, a high quality and accuracy interpolation is obtained. The presented algorithm is robust and has 20 adjustable parameters for use with different modalities. The main advantages of this morphing algorithm are: 1) applicability to general configurations of planes in 3D space, 2) automated behavior, 3) applicability to CT scans with no changes in the algorithm and software. Subsequently, to visualize data, a specialized volume rendering card (TeraRecon VolumePro 1000) was used. To represent data in 3D space, special software was developed to convert interpolated CT slices to 3D objects compatible with the VolumePro card. Quantitative and visual comparison between the proposed model and linear interpolation clearly demonstrates the superiority of the proposed model. Evaluation is performed by removing slices from the original stack of 2D images and using them as reference for error comparison among alternative approaches. Error analysis using average Mean Square and Absolute error clearly demonstrates improved performance