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Segmentation of uterus and myoma from MRI image based on deep learning.

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Title: Segmentation of uterus and myoma from MRI image based on deep learning.
Authors: Lin DQ; Department of Computer Science and Engineering, National Sun Yat-Sen University, Kaohsiung, Taiwan., Yeh LR; Department of Medical Imaging, E-Da Hospital, Kaohsiung, Taiwan., Chang Y; Center for Functional Onco-Imaging, University of California, Irvine, CA, USA., Chen JH; Department of Medical Imaging, E-Da Hospital, Kaohsiung, Taiwan; Center for Functional Onco-Imaging, University of California, Irvine, CA, USA., Yu YC; Department of Obstetrics & Gynecology, E-Da Hospital/I-Shou University, Kaohsiung, Taiwan., Chang CC; E-Da Dachang Hospital/I-Shou University, Kaohsiung, Taiwan. Electronic address: ed101779@edah.org.tw., Chiang JY; Department of Computer Science and Engineering, National Sun Yat-Sen University, Kaohsiung, Taiwan. Electronic address: chiang@cse.nsysu.edu.tw., Huang SJ; Department of Obstetrics & Gynecology, E-Da Hospital/I-Shou University, Kaohsiung, Taiwan; E-Da Dachang Hospital/I-Shou University, Kaohsiung, Taiwan; College of Medicine, I-Shou University, Kaohsiung, Taiwan; Department of Obstetrics & Gynecology, Morsani College of Medicine, University of South Florida, Tampa, FL, USA. Electronic address: huang3@cloud.isu.edu.tw.
Source: Taiwanese journal of obstetrics & gynecology [Taiwan J Obstet Gynecol] 2026 May; Vol. 65 (3), pp. 546-554.
Publication Type: Journal Article
Journal Info: Publisher: Elsevier Country of Publication: China (Republic : 1949- ) NLM ID: 101213819 Publication Model: Print Cited Medium: Internet ISSN: 1875-6263 (Electronic) Linking ISSN: 10284559 NLM ISO Abbreviation: Taiwan J Obstet Gynecol Subsets: MEDLINE
Database: MEDLINE Ultimate
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  Data: Segmentation of uterus and myoma from MRI image based on deep learning.
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  Data: <searchLink fieldCode="AU" term="%22Lin+DQ%22">Lin DQ</searchLink>; Department of Computer Science and Engineering, National Sun Yat-Sen University, Kaohsiung, Taiwan.<br /><searchLink fieldCode="AU" term="%22Yeh+LR%22">Yeh LR</searchLink>; Department of Medical Imaging, E-Da Hospital, Kaohsiung, Taiwan.<br /><searchLink fieldCode="AU" term="%22Chang+Y%22">Chang Y</searchLink>; Center for Functional Onco-Imaging, University of California, Irvine, CA, USA.<br /><searchLink fieldCode="AU" term="%22Chen+JH%22">Chen JH</searchLink>; Department of Medical Imaging, E-Da Hospital, Kaohsiung, Taiwan; Center for Functional Onco-Imaging, University of California, Irvine, CA, USA.<br /><searchLink fieldCode="AU" term="%22Yu+YC%22">Yu YC</searchLink>; Department of Obstetrics & Gynecology, E-Da Hospital/I-Shou University, Kaohsiung, Taiwan.<br /><searchLink fieldCode="AU" term="%22Chang+CC%22">Chang CC</searchLink>; E-Da Dachang Hospital/I-Shou University, Kaohsiung, Taiwan. Electronic address: ed101779@edah.org.tw.<br /><searchLink fieldCode="AU" term="%22Chiang+JY%22">Chiang JY</searchLink>; Department of Computer Science and Engineering, National Sun Yat-Sen University, Kaohsiung, Taiwan. Electronic address: chiang@cse.nsysu.edu.tw.<br /><searchLink fieldCode="AU" term="%22Huang+SJ%22">Huang SJ</searchLink>; Department of Obstetrics & Gynecology, E-Da Hospital/I-Shou University, Kaohsiung, Taiwan; E-Da Dachang Hospital/I-Shou University, Kaohsiung, Taiwan; College of Medicine, I-Shou University, Kaohsiung, Taiwan; Department of Obstetrics & Gynecology, Morsani College of Medicine, University of South Florida, Tampa, FL, USA. Electronic address: huang3@cloud.isu.edu.tw.
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  Data: <searchLink fieldCode="JN" term="%22101213819%22">Taiwanese journal of obstetrics & gynecology</searchLink> [Taiwan J Obstet Gynecol] 2026 May; Vol. 65 (3), pp. 546-554.
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  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Elsevier%22">Elsevier </searchLink><i>Country of Publication: </i>China (Republic : 1949- ) <i>NLM ID: </i>101213819 <i>Publication Model: </i>Print <i>Cited Medium: </i>Internet <i>ISSN: </i>1875-6263 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2210284559%22">10284559 </searchLink><i>NLM ISO Abbreviation: </i>Taiwan J Obstet Gynecol <i>Subsets: </i>MEDLINE
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      – Type: doi
        Value: 10.1016/j.tjog.2024.05.030
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      – Code: eng
        Text: English
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        StartPage: 546
    Titles:
      – TitleFull: Segmentation of uterus and myoma from MRI image based on deep learning.
        Type: main
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            NameFull: Lin DQ
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            NameFull: Yeh LR
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            NameFull: Chang Y
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            NameFull: Chen JH
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            NameFull: Yu YC
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            NameFull: Chang CC
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            NameFull: Chiang JY
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            NameFull: Huang SJ
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            – D: 01
              M: 05
              Text: 2026 May
              Type: published
              Y: 2026
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              Value: 1875-6263
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              Value: 65
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              Value: 3
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            – TitleFull: Taiwanese journal of obstetrics & gynecology
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