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1
Automated segmentation of magnetic resonance bone marrow signal: a feasibility study
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Automated segmentation of magnetic resonance bone marrow signal: a feasibility study

Pediatric radiology, 2022-05, Vol.52 (6), p.1104-1114 [Peer Reviewed Journal]

The Author(s) 2022. corrected publication 2022 ;2022. The Author(s). ;The Author(s) 2022. corrected publication 2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;info:eu-repo/semantics/openAccess ;The Author(s) 2022, corrected publication 2022 ;ISSN: 0301-0449 ;ISSN: 1432-1998 ;EISSN: 1432-1998 ;DOI: 10.1007/s00247-021-05270-x ;PMID: 35107593

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Correction to: Automated segmentation of magnetic resonance bone marrow signal: a feasibility study
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Correction to: Automated segmentation of magnetic resonance bone marrow signal: a feasibility study

Pediatric radiology, 2022-05, Vol.52 (6), p.1196-1196 [Peer Reviewed Journal]

Springer-Verlag GmbH Germany, part of Springer Nature 2022 ;Springer-Verlag GmbH Germany, part of Springer Nature 2022. ;ISSN: 0301-0449 ;EISSN: 1432-1998 ;DOI: 10.1007/s00247-022-05315-9 ;PMID: 35192023

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3
Anam-Net: Anamorphic Depth Embedding-Based Lightweight CNN for Segmentation of Anomalies in COVID-19 Chest CT Images
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Anam-Net: Anamorphic Depth Embedding-Based Lightweight CNN for Segmentation of Anomalies in COVID-19 Chest CT Images

2021 The Author(s) ;ISSN: 2162-237X ;EISSN: 2162-2388 ;DOI: 10.1109/TNNLS.2021.3054746

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4
MRI segmentation of tooth tissue in age prediction of sub-adults — a new method for combining data from the 1st, 2nd, and 3rd molars
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MRI segmentation of tooth tissue in age prediction of sub-adults — a new method for combining data from the 1st, 2nd, and 3rd molars

Navngivelse 4.0 Internasjonal ;ISSN: 0937-9827 ;EISSN: 1437-1596 ;DOI: 10.1007/s00414-023-03149-0

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5
RIL-Contour: a Medical Imaging Dataset Annotation Tool for and with Deep Learning
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RIL-Contour: a Medical Imaging Dataset Annotation Tool for and with Deep Learning

Journal of digital imaging, 2019-08, Vol.32 (4), p.571-581 [Peer Reviewed Journal]

The Author(s) 2019 ;Journal of Digital Imaging is a copyright of Springer, (2019). All Rights Reserved. © 2019. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 0897-1889 ;EISSN: 1618-727X ;DOI: 10.1007/s10278-019-00232-0 ;PMID: 31089974

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6
Prediction of Age Older than 18 Years in Sub-adults by MRI Segmentation of 1st and 2nd Molars
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Prediction of Age Older than 18 Years in Sub-adults by MRI Segmentation of 1st and 2nd Molars

Navngivelse 4.0 Internasjonal ;ISSN: 0937-9827 ;EISSN: 1437-1596 ;DOI: 10.1007/s00414-023-03055-5

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7
Age prediction in sub-adults based on MRI segmentation of 3rd molar tissue volumes
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Age prediction in sub-adults based on MRI segmentation of 3rd molar tissue volumes

Navngivelse 4.0 Internasjonal ;ISSN: 0937-9827 ;EISSN: 1437-1596 ;DOI: 10.1007/s00414-023-02977-4

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8
MRI segmentation of tooth tissue in age prediction of sub-adults — a new method for combining data from the 1st, 2nd, and 3rd molars
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MRI segmentation of tooth tissue in age prediction of sub-adults — a new method for combining data from the 1st, 2nd, and 3rd molars

International journal of legal medicine, 2024-05, Vol.138 (3), p.939-949 [Peer Reviewed Journal]

The Author(s) 2023 ;info:eu-repo/semantics/openAccess ;ISSN: 0937-9827 ;ISSN: 1437-1596 ;EISSN: 1437-1596 ;DOI: 10.1007/s00414-023-03149-0

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9
Prediction of Age Older than 18 Years in Sub-adults by MRI Segmentation of 1st and 2nd Molars
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Prediction of Age Older than 18 Years in Sub-adults by MRI Segmentation of 1st and 2nd Molars

International journal of legal medicine, 2023-09, Vol.137 (5), p.1515-1526 [Peer Reviewed Journal]

The Author(s) 2023 ;info:eu-repo/semantics/openAccess ;ISSN: 0937-9827 ;EISSN: 1437-1596 ;DOI: 10.1007/s00414-023-03055-5

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10
Age prediction in sub-adults based on MRI segmentation of 3rd molar tissue volumes
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Age prediction in sub-adults based on MRI segmentation of 3rd molar tissue volumes

International journal of legal medicine, 2023-05, Vol.137 (3), p.753-763 [Peer Reviewed Journal]

The Author(s) 2023 ;2023. The Author(s). ;The Author(s) 2023. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;info:eu-repo/semantics/openAccess ;ISSN: 0937-9827 ;EISSN: 1437-1596 ;DOI: 10.1007/s00414-023-02977-4 ;PMID: 36811675

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11
Automated segmentation of magnetic resonance bone marrow signal: a feasibility study
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Automated segmentation of magnetic resonance bone marrow signal: a feasibility study

Pediatric radiology, 2022-02 [Peer Reviewed Journal]

info:eu-repo/semantics/openAccess ;ISSN: 0301-0449 ;EISSN: 1432-1998 ;DOI: 10.1007/s00247-022-05315-9

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12
Body composition assessment by artificial intelligence from routine computed tomography scans in colorectal cancer: Introducing BodySegAI
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Body composition assessment by artificial intelligence from routine computed tomography scans in colorectal cancer: Introducing BodySegAI

JCSM clinical reports, 2022-07, Vol.7 (3), p.55-64 [Peer Reviewed Journal]

2022 The Authors. JCSM Clinical Reports published by John Wiley & Sons Ltd on behalf of Society on Sarcopenia, Cachexia and Wasting Disorders. ;2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;info:eu-repo/semantics/openAccess ;ISSN: 2521-3555 ;EISSN: 2521-3555 ;DOI: 10.1002/crt2.53

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13
Quantification of adipose tissues by Dual-Energy X-Ray Absorptiometry and Computed Tomography in colorectal cancer patients
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Quantification of adipose tissues by Dual-Energy X-Ray Absorptiometry and Computed Tomography in colorectal cancer patients

Clinical nutrition ESPEN, 2021-06 [Peer Reviewed Journal]

info:eu-repo/semantics/openAccess ;ISSN: 2405-4577 ;EISSN: 2405-4577 ;DOI: 10.1016/j.clnesp.2021.03.022

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14
Quantification of adipose tissues by Dual-Energy X-Ray Absorptiometry and Computed Tomography in colorectal cancer patients
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Quantification of adipose tissues by Dual-Energy X-Ray Absorptiometry and Computed Tomography in colorectal cancer patients

ISSN: 2405-4577 ;EISSN: 2405-4577 ;DOI: 10.1016/j.clnesp.2021.03.022

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15
Vil radiologer bli erstattet av kunstig intelligens?
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Vil radiologer bli erstattet av kunstig intelligens?

Tidsskrift for den Norske Lægeforening, 2018-10, Vol.138 (17) [Peer Reviewed Journal]

ISSN: 0029-2001 ;EISSN: 0807-7096 ;DOI: 10.4045/tidsskr.18.0587

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16
Will radiologists be replaced by artificial intelligence?
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Will radiologists be replaced by artificial intelligence?

Tidsskrift for den Norske Lægeforening, 2018-10, Vol.138 (17) [Peer Reviewed Journal]

EISSN: 0807-7096 ;DOI: 10.4045/tidsskr.18.0587 ;PMID: 30378411

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17
MRI segmentation of tooth tissue in age prediction of sub-adults — a new method for combining data from the 1st, 2nd, and 3rd molars
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Article
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MRI segmentation of tooth tissue in age prediction of sub-adults — a new method for combining data from the 1st, 2nd, and 3rd molars

info:eu-repo/semantics/openAccess

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18
Age prediction in sub-adults based on MRI segmentation of 3rd molar tissue volumes
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Article
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Age prediction in sub-adults based on MRI segmentation of 3rd molar tissue volumes

info:eu-repo/semantics/openAccess

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19
Prediction of Age Older than 18 Years in Sub-adults by MRI Segmentation of 1st and 2nd Molars
Material Type:
Article
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Prediction of Age Older than 18 Years in Sub-adults by MRI Segmentation of 1st and 2nd Molars

info:eu-repo/semantics/openAccess

Digital Resources/Online E-Resources

20
Anam-Net: Anamorphic Depth Embedding-Based Lightweight CNN for Segmentation of Anomalies in COVID-19 Chest CT Images
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Article
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Anam-Net: Anamorphic Depth Embedding-Based Lightweight CNN for Segmentation of Anomalies in COVID-19 Chest CT Images

info:eu-repo/semantics/openAccess

Digital Resources/Online E-Resources

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