Adnexal torsion diagnosis framework with CT-based adaptive preprocessing and deep neural networks.
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| Title: | Adnexal torsion diagnosis framework with CT-based adaptive preprocessing and deep neural networks. |
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| Authors: | Kim SM; School of Computer Science and Engineering, Kyungpook National University, Daegu, 41566, Republic of Korea., Shin HK; School of Computer Science and Engineering, Kyungpook National University, Daegu, 41566, Republic of Korea., Bae SE; School of Computer Science and Engineering, Kyungpook National University, Daegu, 41566, Republic of Korea., Kim JM; Department of Obstetrics and Gynecology, School of Medicine, Kyungpook National University, Kyungpook National University Chilgok Hospital, Daegu, 41404, Republic of Korea., Lee YH; Department of Obstetrics and Gynecology, School of Medicine, Kyungpook National University, Kyungpook National University Chilgok Hospital, Daegu, 41404, Republic of Korea., Chong GO; Department of Obstetrics and Gynecology, School of Medicine, Kyungpook National University, Kyungpook National University Chilgok Hospital, Daegu, 41404, Republic of Korea., Lee J; Department of Obstetrics and Gynecology, School of Medicine, Kyungpook National University, Kyungpook National University Hospital, Daegu, 41944, Republic of Korea., Park JC; Department of Obstetrics and Gynecology, School of Medicine, Kyungpook National University, Kyungpook National University Hospital, Daegu, 41944, Republic of Korea., Lee HJ; Department of Obstetrics and Gynecology, School of Medicine, Kyungpook National University, Kyungpook National University Hospital, Daegu, 41944, Republic of Korea., Park SY; Department of Radiology, School of Medicine, Kyungpook National University, Kyungpook National University Chilgok Hospital, Daegu, 41404, Republic of Korea., Lee J; Department of Obstetrics and Gynecology, School of Medicine, Kyungpook National University, Kyungpook National University Hospital, Daegu, 41944, Republic of Korea. gyjhlee@knu.ac.kr., Nam WJ; School of Computer Science and Engineering, Kyungpook National University, Daegu, 41566, Republic of Korea. nwj0612@knu.ac.kr. |
| Source: | Scientific reports [Sci Rep] 2026 May 07. Date of Electronic Publication: 2026 May 07. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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