PO-1787 Impact of deep learning segmentation methods on the robustness of MR glioblastoma radiomics. (May 2022)
- Record Type:
- Journal Article
- Title:
- PO-1787 Impact of deep learning segmentation methods on the robustness of MR glioblastoma radiomics. (May 2022)
- Main Title:
- PO-1787 Impact of deep learning segmentation methods on the robustness of MR glioblastoma radiomics
- Authors:
- Vuong, D.
Daetwyler, K.
Bogowicz, M.
Radojewski, P.
Meier, R.
Reyes, M.
Saltybaeva, N.
Depeursinge, A.
Bach, M.
Piccirelli, M.
Guckenberger, M.
Tanadini-Lang, S.
Wies, R. - Abstract:
- Is Part Of:
- Radiotherapy and oncology. Volume 170(2022)Supplement 1
- Journal:
- Radiotherapy and oncology
- Issue:
- Volume 170(2022)Supplement 1
- Issue Display:
- Volume 170, Issue 1 (2022)
- Year:
- 2022
- Volume:
- 170
- Issue:
- 1
- Issue Sort Value:
- 2022-0170-0001-0000
- Page Start:
- S1594
- Page End:
- S1595
- Publication Date:
- 2022-05
- Subjects:
- Oncology -- Periodicals
Radiotherapy -- Periodicals
Tumors -- Periodicals
Medical Oncology -- Periodicals
Neoplasms -- radiotherapy -- Periodicals
Radiotherapy -- Periodicals
Radiothérapie -- Périodiques
Cancérologie -- Périodiques
Tumeurs -- Périodiques
Electronic journals
616.9940642 - Journal URLs:
- http://www.sciencedirect.com/science/journal/01678140 ↗
http://www.clinicalkey.com/dura/browse/journalIssue/01678140 ↗
http://www.clinicalkey.com.au/dura/browse/journalIssue/01678140 ↗
http://www.estro.org/ ↗
http://www.elsevier.com/journals ↗
http://www.journals.elsevier.com/radiotherapy-and-oncology/ ↗ - DOI:
- 10.1016/S0167-8140(22)03751-3 ↗
- Languages:
- English
- ISSNs:
- 0167-8140
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 7240.790000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 21914.xml