Lucas Polson, Pedro Esquinas, Sara Kurkowska, Chenguang Li, Peyman Sheikhzadeh, Mehrshad Abbassi, Saeed Farzanehfar, Seyyede Mirabedian, Carlos Uribe, Arman Rahmim
{"title":"利用一维卷积和旋转在高能量 SPECT 成像中实现快速准确的准直器-探测器响应补偿","authors":"Lucas Polson, Pedro Esquinas, Sara Kurkowska, Chenguang Li, Peyman Sheikhzadeh, Mehrshad Abbassi, Saeed Farzanehfar, Seyyede Mirabedian, Carlos Uribe, Arman Rahmim","doi":"arxiv-2409.03100","DOIUrl":null,"url":null,"abstract":"Modeling of the collimator-detector response (CDR) in SPECT reconstruction\nenables improved resolution and more accurate quantitation, especially for\nhigher energy imaging (e.g.Lu-177 and Ac-225). Such modeling, however, can pose\na significant computational bottleneck when there are substantial components of\nseptal penetration and scatter in the acquired data, since a direct\nconvolution-based approach requires large 2D kernels. The present work presents\nan alternative method for fast and accurate CDR compensation using a linear\noperator built from 1D convolutions and rotations (1D-R). To enable open-source\ndevelopment and use of these models in image reconstruction, we release a\nSPECTPSFToolbox repository for the PyTomography project on GitHub.","PeriodicalId":501378,"journal":{"name":"arXiv - PHYS - Medical Physics","volume":"46 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Fast and Accurate Collimator-Detector Response Compensation in High-Energy SPECT Imaging with 1D Convolutions and Rotations\",\"authors\":\"Lucas Polson, Pedro Esquinas, Sara Kurkowska, Chenguang Li, Peyman Sheikhzadeh, Mehrshad Abbassi, Saeed Farzanehfar, Seyyede Mirabedian, Carlos Uribe, Arman Rahmim\",\"doi\":\"arxiv-2409.03100\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Modeling of the collimator-detector response (CDR) in SPECT reconstruction\\nenables improved resolution and more accurate quantitation, especially for\\nhigher energy imaging (e.g.Lu-177 and Ac-225). Such modeling, however, can pose\\na significant computational bottleneck when there are substantial components of\\nseptal penetration and scatter in the acquired data, since a direct\\nconvolution-based approach requires large 2D kernels. The present work presents\\nan alternative method for fast and accurate CDR compensation using a linear\\noperator built from 1D convolutions and rotations (1D-R). To enable open-source\\ndevelopment and use of these models in image reconstruction, we release a\\nSPECTPSFToolbox repository for the PyTomography project on GitHub.\",\"PeriodicalId\":501378,\"journal\":{\"name\":\"arXiv - PHYS - Medical Physics\",\"volume\":\"46 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-09-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - PHYS - Medical Physics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2409.03100\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - PHYS - Medical Physics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2409.03100","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Fast and Accurate Collimator-Detector Response Compensation in High-Energy SPECT Imaging with 1D Convolutions and Rotations
Modeling of the collimator-detector response (CDR) in SPECT reconstruction
enables improved resolution and more accurate quantitation, especially for
higher energy imaging (e.g.Lu-177 and Ac-225). Such modeling, however, can pose
a significant computational bottleneck when there are substantial components of
septal penetration and scatter in the acquired data, since a direct
convolution-based approach requires large 2D kernels. The present work presents
an alternative method for fast and accurate CDR compensation using a linear
operator built from 1D convolutions and rotations (1D-R). To enable open-source
development and use of these models in image reconstruction, we release a
SPECTPSFToolbox repository for the PyTomography project on GitHub.