{"title":"Deep learning convolutional neural network (DLCNN): unleashing the potential of <sup>18</sup>F-FDG PET/CT in lymphoma.","authors":"Ke Li, Ran Zhang, Weibo Cai","doi":"","DOIUrl":null,"url":null,"abstract":"<p><p>This perspective briefly reviewed the applications of <sup>18</sup>F-FDG PET/CT in the clinical management of lymphoma and the need for lesion segmentation in those applications. It discussed the limitations of existing segmentation technologies and the great potential of using deep learning convolutional neural network (DLCNN) to accomplish automatic lymphoma segmentation and characterizations. Finally, the authors shared perspectives on the technical challenges that need to be addressed to fully unleash the potential of DLCNN and <sup>18</sup>F-FDG PET/CT in the diagnosis, prognosis, and treatment of lymphoma.</p>","PeriodicalId":7572,"journal":{"name":"American journal of nuclear medicine and molecular imaging","volume":"11 4","pages":"327-331"},"PeriodicalIF":2.0000,"publicationDate":"2021-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8414402/pdf/ajnmmi0011-0327.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"American journal of nuclear medicine and molecular imaging","FirstCategoryId":"1085","ListUrlMain":"","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2021/1/1 0:00:00","PubModel":"eCollection","JCR":"Q3","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}
引用次数: 0
Abstract
This perspective briefly reviewed the applications of 18F-FDG PET/CT in the clinical management of lymphoma and the need for lesion segmentation in those applications. It discussed the limitations of existing segmentation technologies and the great potential of using deep learning convolutional neural network (DLCNN) to accomplish automatic lymphoma segmentation and characterizations. Finally, the authors shared perspectives on the technical challenges that need to be addressed to fully unleash the potential of DLCNN and 18F-FDG PET/CT in the diagnosis, prognosis, and treatment of lymphoma.
期刊介绍：
The scope of AJNMMI encompasses all areas of molecular imaging, including but not limited to: positron emission tomography (PET), single-photon emission computed tomography (SPECT), molecular magnetic resonance imaging, magnetic resonance spectroscopy, optical bioluminescence, optical fluorescence, targeted ultrasound, photoacoustic imaging, etc. AJNMMI welcomes original and review articles on both clinical investigation and preclinical research. Occasionally, special topic issues, short communications, editorials, and invited perspectives will also be published. Manuscripts, including figures and tables, must be original and not under consideration by another journal.
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