{"title":"大体积光学分辨率光声显微镜的三维融合","authors":"Xiongjun Cao, Zhihui Li, Xianlin Song","doi":"10.1117/12.2603388","DOIUrl":null,"url":null,"abstract":"Photoacoustic imaging has gradually developed into a new and important imaging technology. As an important branch of photoacoustic imaging, optical-resolution photoacoustic microscopy combines the advantages of optical imaging and acoustic imaging, it has the advantages of high resolution, high contrast, high sensitivity and so on. However, in order to obtain high resolution, it is often necessary to focus the laser beam strongly, which will lead to the small depth of field and the inability to obtain large-scale structural information. However, in clinical diagnosis, doctors hope to obtain large-scale, high-resolution structural and functional information as much as possible, so it is of great significance to solve the problem of small depth of field in photoacoustic microscopy. Here, we proposed three-dimensional fusion for large volumetric optical-resolution photoacoustic microscopy. Firstly, two groups of virtual cerebral vascular 3D photoacoustic data obtained at different focal locations were obtained by using virtual photoacoustic microscopic imaging platform. Then, based on the multi-scale weight gradient fusion algorithm, the B-scan data of mouse cerebrovascular data were fused, and the maximum projection reduction was performed on the fused 3D data. Finally, the images before and after fusion were compared. Experimental results show that this algorithm can effectively obtain large volumetric and high-resolution photoacoustic images.","PeriodicalId":330466,"journal":{"name":"Sixteenth National Conference on Laser Technology and Optoelectronics","volume":"176 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Three-dimensional fusion for large volumetric optical-resolution photoacoustic microscopy\",\"authors\":\"Xiongjun Cao, Zhihui Li, Xianlin Song\",\"doi\":\"10.1117/12.2603388\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Photoacoustic imaging has gradually developed into a new and important imaging technology. As an important branch of photoacoustic imaging, optical-resolution photoacoustic microscopy combines the advantages of optical imaging and acoustic imaging, it has the advantages of high resolution, high contrast, high sensitivity and so on. However, in order to obtain high resolution, it is often necessary to focus the laser beam strongly, which will lead to the small depth of field and the inability to obtain large-scale structural information. However, in clinical diagnosis, doctors hope to obtain large-scale, high-resolution structural and functional information as much as possible, so it is of great significance to solve the problem of small depth of field in photoacoustic microscopy. Here, we proposed three-dimensional fusion for large volumetric optical-resolution photoacoustic microscopy. Firstly, two groups of virtual cerebral vascular 3D photoacoustic data obtained at different focal locations were obtained by using virtual photoacoustic microscopic imaging platform. Then, based on the multi-scale weight gradient fusion algorithm, the B-scan data of mouse cerebrovascular data were fused, and the maximum projection reduction was performed on the fused 3D data. Finally, the images before and after fusion were compared. Experimental results show that this algorithm can effectively obtain large volumetric and high-resolution photoacoustic images.\",\"PeriodicalId\":330466,\"journal\":{\"name\":\"Sixteenth National Conference on Laser Technology and Optoelectronics\",\"volume\":\"176 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-08-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Sixteenth National Conference on Laser Technology and Optoelectronics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1117/12.2603388\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sixteenth National Conference on Laser Technology and Optoelectronics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.2603388","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Three-dimensional fusion for large volumetric optical-resolution photoacoustic microscopy
Photoacoustic imaging has gradually developed into a new and important imaging technology. As an important branch of photoacoustic imaging, optical-resolution photoacoustic microscopy combines the advantages of optical imaging and acoustic imaging, it has the advantages of high resolution, high contrast, high sensitivity and so on. However, in order to obtain high resolution, it is often necessary to focus the laser beam strongly, which will lead to the small depth of field and the inability to obtain large-scale structural information. However, in clinical diagnosis, doctors hope to obtain large-scale, high-resolution structural and functional information as much as possible, so it is of great significance to solve the problem of small depth of field in photoacoustic microscopy. Here, we proposed three-dimensional fusion for large volumetric optical-resolution photoacoustic microscopy. Firstly, two groups of virtual cerebral vascular 3D photoacoustic data obtained at different focal locations were obtained by using virtual photoacoustic microscopic imaging platform. Then, based on the multi-scale weight gradient fusion algorithm, the B-scan data of mouse cerebrovascular data were fused, and the maximum projection reduction was performed on the fused 3D data. Finally, the images before and after fusion were compared. Experimental results show that this algorithm can effectively obtain large volumetric and high-resolution photoacoustic images.