NIR-II/NIR-I Fluorescence Molecular Tomography of Heterogeneous Mice Based on Gaussian Weighted Neighborhood Fused Lasso Method
Fluorescence molecular tomography (FMT), which can visualize the distribution of fluorescence biomarkers, has become a novel three-dimensional noninvasive imaging technique for in vivo studies such as tumor detection and lymph node location. However, it remains a challenging problem to achieve satis...
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Veröffentlicht in: | IEEE transactions on medical imaging 2020-06, Vol.39 (6), p.2213-2222 |
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description | Fluorescence molecular tomography (FMT), which can visualize the distribution of fluorescence biomarkers, has become a novel three-dimensional noninvasive imaging technique for in vivo studies such as tumor detection and lymph node location. However, it remains a challenging problem to achieve satisfactory reconstruction performance of conventional FMT in the first near-infrared window (NIR-I, 700-900nm) because of the severe scattering of NIR-I light. In this study, a promising FMT method for heterogeneous mice was proposed to improve the reconstruction accuracy using the second near-infrared window (NIR-II, 1000-1700nm), where the light scattering significantly reduced compared with NIR-I. The optical properties of NIR-II were analyzed to construct the forward model for NIR-II FMT. Furthermore, to raise the accuracy of solution of the inverse problem, we proposed a novel Gaussian weighted neighborhood fused Lasso (GWNFL) method. Numerical simulation was performed to demonstrate the outperformance of GWNFL compared with other algorithms. Besides, a novel NIR-II/NIR-I dual-modality FMT system was developed to contrast the in vivo reconstruction performance between NIR-II FMT and NIR-I FMT. To compare the reconstruction performance of NIR-II FMT with traditional NIR-I FMT, numerical simulations and in vivo experiments were conducted. Both the simulation and in vivo results showed that NIR-II FMT outperformed NIR-I FMT in terms of location accuracy and spatial overlap index. It is believed that this study could promote the development and biomedical application of NIR-II FMT in the future. |
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However, it remains a challenging problem to achieve satisfactory reconstruction performance of conventional FMT in the first near-infrared window (NIR-I, 700-900nm) because of the severe scattering of NIR-I light. In this study, a promising FMT method for heterogeneous mice was proposed to improve the reconstruction accuracy using the second near-infrared window (NIR-II, 1000-1700nm), where the light scattering significantly reduced compared with NIR-I. The optical properties of NIR-II were analyzed to construct the forward model for NIR-II FMT. Furthermore, to raise the accuracy of solution of the inverse problem, we proposed a novel Gaussian weighted neighborhood fused Lasso (GWNFL) method. Numerical simulation was performed to demonstrate the outperformance of GWNFL compared with other algorithms. Besides, a novel NIR-II/NIR-I dual-modality FMT system was developed to contrast the in vivo reconstruction performance between NIR-II FMT and NIR-I FMT. To compare the reconstruction performance of NIR-II FMT with traditional NIR-I FMT, numerical simulations and in vivo experiments were conducted. Both the simulation and in vivo results showed that NIR-II FMT outperformed NIR-I FMT in terms of location accuracy and spatial overlap index. It is believed that this study could promote the development and biomedical application of NIR-II FMT in the future.</description><identifier>ISSN: 0278-0062</identifier><identifier>EISSN: 1558-254X</identifier><identifier>DOI: 10.1109/TMI.2020.2964853</identifier><identifier>PMID: 31976880</identifier><identifier>CODEN: ITMID4</identifier><language>eng</language><publisher>United States: IEEE</publisher><subject>Accuracy ; Algorithms ; Biomarkers ; Biomedical materials ; Biomedical optical imaging ; Computer simulation ; Fluorescence ; Fluorescence molecular tomography ; GWNFL method ; I.R. radiation ; Image reconstruction ; Imaging techniques ; In vivo ; In vivo methods and tests ; Infrared windows ; Inverse problems ; Light scattering ; Lymph nodes ; Mathematical models ; Molecular imaging ; Near infrared radiation ; NIR-I ; NIR-II ; Optical properties ; Optical scattering ; Reconstruction ; Tomography</subject><ispartof>IEEE transactions on medical imaging, 2020-06, Vol.39 (6), p.2213-2222</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. 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However, it remains a challenging problem to achieve satisfactory reconstruction performance of conventional FMT in the first near-infrared window (NIR-I, 700-900nm) because of the severe scattering of NIR-I light. In this study, a promising FMT method for heterogeneous mice was proposed to improve the reconstruction accuracy using the second near-infrared window (NIR-II, 1000-1700nm), where the light scattering significantly reduced compared with NIR-I. The optical properties of NIR-II were analyzed to construct the forward model for NIR-II FMT. Furthermore, to raise the accuracy of solution of the inverse problem, we proposed a novel Gaussian weighted neighborhood fused Lasso (GWNFL) method. Numerical simulation was performed to demonstrate the outperformance of GWNFL compared with other algorithms. Besides, a novel NIR-II/NIR-I dual-modality FMT system was developed to contrast the in vivo reconstruction performance between NIR-II FMT and NIR-I FMT. To compare the reconstruction performance of NIR-II FMT with traditional NIR-I FMT, numerical simulations and in vivo experiments were conducted. Both the simulation and in vivo results showed that NIR-II FMT outperformed NIR-I FMT in terms of location accuracy and spatial overlap index. It is believed that this study could promote the development and biomedical application of NIR-II FMT in the future.</description><subject>Accuracy</subject><subject>Algorithms</subject><subject>Biomarkers</subject><subject>Biomedical materials</subject><subject>Biomedical optical imaging</subject><subject>Computer simulation</subject><subject>Fluorescence</subject><subject>Fluorescence molecular tomography</subject><subject>GWNFL method</subject><subject>I.R. radiation</subject><subject>Image reconstruction</subject><subject>Imaging techniques</subject><subject>In vivo</subject><subject>In vivo methods and tests</subject><subject>Infrared windows</subject><subject>Inverse problems</subject><subject>Light scattering</subject><subject>Lymph nodes</subject><subject>Mathematical models</subject><subject>Molecular imaging</subject><subject>Near infrared radiation</subject><subject>NIR-I</subject><subject>NIR-II</subject><subject>Optical properties</subject><subject>Optical scattering</subject><subject>Reconstruction</subject><subject>Tomography</subject><issn>0278-0062</issn><issn>1558-254X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>ESBDL</sourceid><sourceid>RIE</sourceid><recordid>eNpdkU1v2zAMQIVhw5q1uw8YMAjYZRenoj5s6bgVS2sgaYEixXYTZJtOXDhWKtmHnvbXpzRZDzuRIB8JEo-QT8DmAMxcrlflnDPO5tzkUivxhsxAKZ1xJX-_JTPGC50xlvMz8iHGR8ZAKmbekzMBpsi1ZjPy57a8z8ry8iXQRT_5gLHGoUa68j3WU-8CXfud3wS33z5T39IbHDH4DQ7op0hXXUJ_uIgN9QO9dlOMnRvoL-w22zEVbw9J5cPW-4YupgO3dDF6usJx65sL8q51fcSPp3hOHhY_11c32fLuurz6vsxqqdSYccyrpioMA27QgdEGHJfCCFEXtW5yBKyMMrpoAYFLbJqmBRBKCdDatK04J9-Oe_fBP00YR7vr0p99717esFxIyfMCdJHQr_-hj34KQ7rOcsmM0BJAJYodqTr4GAO2dh-6nQvPFpg9yLFJjj3IsSc5aeTLafFU7bB5HfhnIwGfj0CHiK9tbXIORoq_Y5KSEQ</recordid><startdate>20200601</startdate><enddate>20200601</enddate><creator>Cai, Meishan</creator><creator>Zhang, Zeyu</creator><creator>Shi, Xiaojing</creator><creator>Hu, Zhenhua</creator><creator>Tian, Jie</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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Zhang, Zeyu ; Shi, Xiaojing ; Hu, Zhenhua ; Tian, Jie</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c455t-2e6bdb790129ea19891a243933c7c8d6e1eb95987f1e124edddf1135531889ff3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Accuracy</topic><topic>Algorithms</topic><topic>Biomarkers</topic><topic>Biomedical materials</topic><topic>Biomedical optical imaging</topic><topic>Computer simulation</topic><topic>Fluorescence</topic><topic>Fluorescence molecular tomography</topic><topic>GWNFL method</topic><topic>I.R. radiation</topic><topic>Image reconstruction</topic><topic>Imaging techniques</topic><topic>In vivo</topic><topic>In vivo methods and tests</topic><topic>Infrared windows</topic><topic>Inverse problems</topic><topic>Light scattering</topic><topic>Lymph nodes</topic><topic>Mathematical models</topic><topic>Molecular imaging</topic><topic>Near infrared radiation</topic><topic>NIR-I</topic><topic>NIR-II</topic><topic>Optical properties</topic><topic>Optical scattering</topic><topic>Reconstruction</topic><topic>Tomography</topic><toplevel>online_resources</toplevel><creatorcontrib>Cai, Meishan</creatorcontrib><creatorcontrib>Zhang, Zeyu</creatorcontrib><creatorcontrib>Shi, Xiaojing</creatorcontrib><creatorcontrib>Hu, Zhenhua</creatorcontrib><creatorcontrib>Tian, Jie</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE Open Access Journals</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Aluminium Industry Abstracts</collection><collection>Biotechnology Research Abstracts</collection><collection>Ceramic Abstracts</collection><collection>Computer and Information Systems Abstracts</collection><collection>Corrosion Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Engineered Materials Abstracts</collection><collection>Materials Business File</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Materials Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Nursing & Allied Health Premium</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>IEEE transactions on medical imaging</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Cai, Meishan</au><au>Zhang, Zeyu</au><au>Shi, Xiaojing</au><au>Hu, Zhenhua</au><au>Tian, Jie</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>NIR-II/NIR-I Fluorescence Molecular Tomography of Heterogeneous Mice Based on Gaussian Weighted Neighborhood Fused Lasso Method</atitle><jtitle>IEEE transactions on medical imaging</jtitle><stitle>TMI</stitle><addtitle>IEEE Trans Med Imaging</addtitle><date>2020-06-01</date><risdate>2020</risdate><volume>39</volume><issue>6</issue><spage>2213</spage><epage>2222</epage><pages>2213-2222</pages><issn>0278-0062</issn><eissn>1558-254X</eissn><coden>ITMID4</coden><abstract>Fluorescence molecular tomography (FMT), which can visualize the distribution of fluorescence biomarkers, has become a novel three-dimensional noninvasive imaging technique for in vivo studies such as tumor detection and lymph node location. However, it remains a challenging problem to achieve satisfactory reconstruction performance of conventional FMT in the first near-infrared window (NIR-I, 700-900nm) because of the severe scattering of NIR-I light. In this study, a promising FMT method for heterogeneous mice was proposed to improve the reconstruction accuracy using the second near-infrared window (NIR-II, 1000-1700nm), where the light scattering significantly reduced compared with NIR-I. The optical properties of NIR-II were analyzed to construct the forward model for NIR-II FMT. Furthermore, to raise the accuracy of solution of the inverse problem, we proposed a novel Gaussian weighted neighborhood fused Lasso (GWNFL) method. Numerical simulation was performed to demonstrate the outperformance of GWNFL compared with other algorithms. Besides, a novel NIR-II/NIR-I dual-modality FMT system was developed to contrast the in vivo reconstruction performance between NIR-II FMT and NIR-I FMT. To compare the reconstruction performance of NIR-II FMT with traditional NIR-I FMT, numerical simulations and in vivo experiments were conducted. Both the simulation and in vivo results showed that NIR-II FMT outperformed NIR-I FMT in terms of location accuracy and spatial overlap index. It is believed that this study could promote the development and biomedical application of NIR-II FMT in the future.</abstract><cop>United States</cop><pub>IEEE</pub><pmid>31976880</pmid><doi>10.1109/TMI.2020.2964853</doi><tpages>10</tpages><orcidid>https://orcid.org/0000-0003-0498-0432</orcidid><orcidid>https://orcid.org/0000-0001-9311-432X</orcidid><orcidid>https://orcid.org/0000-0002-4035-4028</orcidid><orcidid>https://orcid.org/0000-0002-4600-3405</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Accuracy Algorithms Biomarkers Biomedical materials Biomedical optical imaging Computer simulation Fluorescence Fluorescence molecular tomography GWNFL method I.R. radiation Image reconstruction Imaging techniques In vivo In vivo methods and tests Infrared windows Inverse problems Light scattering Lymph nodes Mathematical models Molecular imaging Near infrared radiation NIR-I NIR-II Optical properties Optical scattering Reconstruction Tomography |
title | NIR-II/NIR-I Fluorescence Molecular Tomography of Heterogeneous Mice Based on Gaussian Weighted Neighborhood Fused Lasso Method |
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