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However, FDG-PET\/CT often encounters false positives in tumor detection due to <jats:sup>18<\/jats:sup>fluorodeoxyglucose (FDG) accumulation from the heart and bladder that often exhibit similar FDG uptake as tumors. Thus, it is necessary to eliminate this source of physiological noise. Major challenges for this task include: (1) large inter-patient variability in the appearance for the heart and bladder. (2) The size and shape of bladder or heart may appear different on PET and CT. (3) Tumors can be very close or connected to the heart or bladder.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Approach<\/jats:title>\n                <jats:p>A deep learning based approach is proposed to segment the heart and bladder on whole body PET\/CT automatically. Two 3D U-Nets were developed separately to segment the heart and bladder, where each network receives the PET and CT as a multi-modal input. Data sets were obtained from retrospective clinical trials and include 575 PET\/CT for heart segmentation and 538 for bladder segmentation.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>The models were evaluated on a test set from an independent trial and achieved a Dice Similarity Coefficient (DSC) of 0.96 for heart segmentation and 0.95 for bladder segmentation, Average Surface Distance (ASD) of 0.44\u00a0mm on heart and 0.90\u00a0mm on bladder.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusions<\/jats:title>\n                <jats:p>This methodology could be a valuable component to the FDG-PET\/CT data processing chain by removing FDG physiological noise associated with heart and\/or bladder accumulation prior to image analysis by manual, semi- or automated tumor analysis methods.<\/jats:p>\n              <\/jats:sec>","DOI":"10.1186\/s12880-022-00785-7","type":"journal-article","created":{"date-parts":[[2022,3,30]],"date-time":"2022-03-30T15:10:21Z","timestamp":1648653021000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Heart and bladder detection and segmentation on FDG PET\/CT by deep learning"],"prefix":"10.1186","volume":"22","author":[{"given":"Xiaoyong","family":"Wang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Skander","family":"Jemaa","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jill","family":"Fredrickson","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alexandre Fernandez","family":"Coimbra","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tina","family":"Nielsen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alex","family":"De Crespigny","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Thomas","family":"Bengtsson","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Richard A. 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The trials were conducted in accordance with the Declaration of Helsinki and the International Conference on Harmonization of Good Clinical Practice guidelines. The trials protocol approval was obtained from the ethics committee\/institutional review board at each participating institution, and written informed consent to participate was provided by all patients. The retrospective analysis of this data presented in this manuscript was approved by Genentech Data Governance Committee (Genentech Inc) and is consistent with the intended use of this data defined by the original ethics committee\/institutional review board at each participating institution and the written informed consent provided by all patients.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The only potential conflicts of interest that may be relevant is that all authors are employees and stockholders in Roche\/Genentech.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"58"}}