Habitat-radiomics combining multichannel 2.5D deep learning for differentiating adrenal adenomas from metastases using automatic segmentation: a multicenter study.

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Title: Habitat-radiomics combining multichannel 2.5D deep learning for differentiating adrenal adenomas from metastases using automatic segmentation: a multicenter study.
Authors: Yin S; Department of Radiology, Suzhou Ninth Hospital Affiliated to Soochow University, Suzhou Ninth People's Hospital, Suzhou, China., Ding N; Department of Radiology, Suzhou Ninth Hospital Affiliated to Soochow University, Suzhou Ninth People's Hospital, Suzhou, China., Yang C; Department of Traditional Chinese Medicine, Suzhou Ninth Hospital Affiliated to Soochow University, Suzhou Ninth People's Hospital, Suzhou, China., Wang S; Department of Radiology, Suzhou Ninth Hospital Affiliated to Soochow University, Suzhou Ninth People's Hospital, Suzhou, China., Li M; Department of Radiology, Suzhou Ninth Hospital Affiliated to Soochow University, Suzhou Ninth People's Hospital, Suzhou, China., Ji Y; Department of Radiology, Suzhou Ninth Hospital Affiliated to Soochow University, Suzhou Ninth People's Hospital, Suzhou, China., Liu T; Department of Obstetrics and Gynecology, Xuzhou Central Hospital, Xuzhou, China., Jin L; Department of Radiology, Suzhou Ninth Hospital Affiliated to Soochow University, Suzhou Ninth People's Hospital, Suzhou, China.
Source: Frontiers in endocrinology [Front Endocrinol (Lausanne)] 2026 Jun 12; Vol. 17, pp. 1794301. Date of Electronic Publication: 2026 Jun 12 (Print Publication: 2026).
Publication Type: Journal Article; Multicenter Study
Journal Info: Publisher: Frontiers Research Foundation] Country of Publication: Switzerland NLM ID: 101555782 Publication Model: eCollection Cited Medium: Print ISSN: 1664-2392 (Print) Linking ISSN: 16642392 NLM ISO Abbreviation: Front Endocrinol (Lausanne) Subsets: MEDLINE
Database: MEDLINE Ultimate
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  Data: Habitat-radiomics combining multichannel 2.5D deep learning for differentiating adrenal adenomas from metastases using automatic segmentation: a multicenter study.
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  Data: <searchLink fieldCode="AU" term="%22Yin+S%22">Yin S</searchLink>; Department of Radiology, Suzhou Ninth Hospital Affiliated to Soochow University, Suzhou Ninth People's Hospital, Suzhou, China.<br /><searchLink fieldCode="AU" term="%22Ding+N%22">Ding N</searchLink>; Department of Radiology, Suzhou Ninth Hospital Affiliated to Soochow University, Suzhou Ninth People's Hospital, Suzhou, China.<br /><searchLink fieldCode="AU" term="%22Yang+C%22">Yang C</searchLink>; Department of Traditional Chinese Medicine, Suzhou Ninth Hospital Affiliated to Soochow University, Suzhou Ninth People's Hospital, Suzhou, China.<br /><searchLink fieldCode="AU" term="%22Wang+S%22">Wang S</searchLink>; Department of Radiology, Suzhou Ninth Hospital Affiliated to Soochow University, Suzhou Ninth People's Hospital, Suzhou, China.<br /><searchLink fieldCode="AU" term="%22Li+M%22">Li M</searchLink>; Department of Radiology, Suzhou Ninth Hospital Affiliated to Soochow University, Suzhou Ninth People's Hospital, Suzhou, China.<br /><searchLink fieldCode="AU" term="%22Ji+Y%22">Ji Y</searchLink>; Department of Radiology, Suzhou Ninth Hospital Affiliated to Soochow University, Suzhou Ninth People's Hospital, Suzhou, China.<br /><searchLink fieldCode="AU" term="%22Liu+T%22">Liu T</searchLink>; Department of Obstetrics and Gynecology, Xuzhou Central Hospital, Xuzhou, China.<br /><searchLink fieldCode="AU" term="%22Jin+L%22">Jin L</searchLink>; Department of Radiology, Suzhou Ninth Hospital Affiliated to Soochow University, Suzhou Ninth People's Hospital, Suzhou, China.
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  Data: <searchLink fieldCode="JN" term="%22101555782%22">Frontiers in endocrinology</searchLink> [Front Endocrinol (Lausanne)] 2026 Jun 12; Vol. 17, pp. 1794301. <i>Date of Electronic Publication: </i>2026 Jun 12 (<i>Print Publication: </i>2026).
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  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Frontiers+Research+Foundation]%22">Frontiers Research Foundation] </searchLink><i>Country of Publication: </i>Switzerland <i>NLM ID: </i>101555782 <i>Publication Model: </i>eCollection <i>Cited Medium: </i>Print <i>ISSN: </i>1664-2392 (Print) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2216642392%22">16642392 </searchLink><i>NLM ISO Abbreviation: </i>Front Endocrinol (Lausanne) <i>Subsets: </i>MEDLINE
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        Value: 10.3389/fendo.2026.1794301
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        Text: English
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      – TitleFull: Habitat-radiomics combining multichannel 2.5D deep learning for differentiating adrenal adenomas from metastases using automatic segmentation: a multicenter study.
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              Text: 2026 Jun 12
              Type: published
              Y: 2026
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