{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,8]],"date-time":"2026-05-08T08:37:49Z","timestamp":1778229469322,"version":"3.51.4"},"reference-count":28,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2024,1,17]],"date-time":"2024-01-17T00:00:00Z","timestamp":1705449600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2024,1,17]],"date-time":"2024-01-17T00:00:00Z","timestamp":1705449600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int J CARS"],"abstract":"Abstract<\/jats:title>\n Purpose<\/jats:title>\n Edema, or swelling, is a common symptom of kidney, heart, and liver disease. Volumetric edema measurement is potentially clinically useful. Edema can occur in various tissues. This work focuses on segmentation and volume measurement of one common site, subcutaneous adipose tissue.<\/jats:p>\n <\/jats:sec>\n Methods<\/jats:title>\n The density distributions of edema and subcutaneous adipose tissue are represented as a two-class Gaussian mixture model (GMM). In previous work, edema regions were segmented by selecting voxels with density values within the edema density distribution. This work improves upon the prior work by generating an adipose tissue mask without edema through a conditional generative adversarial network. The density distribution of the generated mask was imported into a Chan-Vese level set framework. Edema and subcutaneous adipose tissue are separated by iteratively updating their respective density distributions.<\/jats:p>\n <\/jats:sec>\n Results<\/jats:title>\n Validation results on 25 patients with edema showed that the segmentation accuracy significantly improved. Compared to GMM, the average Dice Similarity Coefficient increased from 56.0 to 61.7% ($$p<0.05$$<\/jats:tex-math>\n \n p<\/mml:mi>\n <<\/mml:mo>\n 0.05<\/mml:mn>\n <\/mml:mrow>\n <\/mml:math><\/jats:alternatives><\/jats:inline-formula>) and the relative volume difference decreased from 36.5 to 30.2% ($$p<0.05$$<\/jats:tex-math>\n \n p<\/mml:mi>\n <<\/mml:mo>\n 0.05<\/mml:mn>\n <\/mml:mrow>\n <\/mml:math><\/jats:alternatives><\/jats:inline-formula>).<\/jats:p>\n <\/jats:sec>\n Conclusion<\/jats:title>\n The generated adipose tissue density prior improved edema segmentation accuracy. Accurate edema volume measurement may prove clinically useful.<\/jats:p>\n <\/jats:sec>","DOI":"10.1007\/s11548-023-03051-5","type":"journal-article","created":{"date-parts":[[2024,1,17]],"date-time":"2024-01-17T19:02:06Z","timestamp":1705518126000},"page":"443-448","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Improved subcutaneous edema segmentation on abdominal CT using a generated adipose tissue density prior"],"prefix":"10.1007","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9885-1695","authenticated-orcid":false,"given":"Jianfei","family":"Liu","sequence":"first","affiliation":[]},{"given":"Omid","family":"Shafaat","sequence":"additional","affiliation":[]},{"given":"Sayantan","family":"Bhadra","sequence":"additional","affiliation":[]},{"given":"Christopher","family":"Parnell","sequence":"additional","affiliation":[]},{"given":"Ayden","family":"Harris","sequence":"additional","affiliation":[]},{"given":"Ronald M.","family":"Summers","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,1,17]]},"reference":[{"issue":"2","key":"3051_CR1","first-page":"102","volume":"88","author":"KP Trayes","year":"2013","unstructured":"Trayes KP, Studiford JS, Pickle S, Tully AS (2013) Edema: diagnosis and management. 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Summers receives royalties from iCAD, Philips, PingAn, ScanMed, and Translation Holdings. His lab received research support from PingAn. The authors have no additional conflict of interest to declare.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"The study was approved by the IRB of the National Institutes of Health and was performed in accordance with the ethical standards as laid down in the 1964 Declaration of Helsinki and its later amendments.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval"}},{"value":"The need for written informed consent waived by the IRB.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent to participate"}}]}}