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Choi, Hanseung, Jeon, Kug Jin, Kim, Young Hyun, Ha, Eun-Gyu, Lee, Chena, Han, Sang-Sun (2022) Deep learning-based fully automatic segmentation of the maxillary sinus on cone-beam computed tomographic images. Scientific Reports, 12 (1) doi:10.1038/s41598-022-18436-w

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Reference TypeJournal (article/letter/editorial)
TitleDeep learning-based fully automatic segmentation of the maxillary sinus on cone-beam computed tomographic images
JournalScientific Reports
AuthorsChoi, HanseungAuthor
Jeon, Kug JinAuthor
Kim, Young HyunAuthor
Ha, Eun-GyuAuthor
Lee, ChenaAuthor
Han, Sang-SunAuthor
Year2022 (August 17)Volume12
Issue1
PublisherSpringer Science and Business Media LLC
DOIdoi:10.1038/s41598-022-18436-wSearch in ResearchGate
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Mindat Ref. ID15213368Long-form Identifiermindat:1:5:15213368:1
GUID0
Full ReferenceChoi, Hanseung, Jeon, Kug Jin, Kim, Young Hyun, Ha, Eun-Gyu, Lee, Chena, Han, Sang-Sun (2022) Deep learning-based fully automatic segmentation of the maxillary sinus on cone-beam computed tomographic images. Scientific Reports, 12 (1) doi:10.1038/s41598-022-18436-w
Plain TextChoi, Hanseung, Jeon, Kug Jin, Kim, Young Hyun, Ha, Eun-Gyu, Lee, Chena, Han, Sang-Sun (2022) Deep learning-based fully automatic segmentation of the maxillary sinus on cone-beam computed tomographic images. Scientific Reports, 12 (1) doi:10.1038/s41598-022-18436-w
In(2022, December) Scientific Reports Vol. 12 (1) Springer Science and Business Media LLC

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