Performance of an advanced deep learning model in fully automated detection and segmentation of primary cerebral lymphoma using multiparametric MRI

Authors :: Goertz, L
Borggrefe, J
Caldeira, LL
Hoyer, C
Goldbrunner, RH
Krischek, B
Laukamp, KR
Pennig, L
Source :: 71. Jahrestagung der Deutschen Gesellschaft für Neurochirurgie (DGNC), 9. Joint Meeting mit der Japanischen Gesellschaft für Neurochirurgie; 20200621-20200624; sine loco [digital]; DOCV269 /20200626/
Publication Year :: 2020
Publisher :: German Medical Science GMS Publishing House, 2020.
Abstract: Objective: Magnetic resonance imaging (MRI) is the imaging modality of choice for detection of primary cerebral lymphoma. After initiating therapy, follow-up MRI scans are necessary to evaluate treatment response. An automated detection and segmentation of the (residual) lymphoma would provide additional[for full text, please go to the a.m. URL]<br />71. Jahrestagung der Deutschen Gesellschaft für Neurochirurgie (DGNC), 9. Joint Meeting mit der Japanischen Gesellschaft für Neurochirurgie

Subjects :: ddc: 610
hemic and lymphatic diseases
610 Medical sciences
Medicine

Language :: English
Database :: OpenAIRE
Journal :: 71. Jahrestagung der Deutschen Gesellschaft für Neurochirurgie (DGNC), 9. Joint Meeting mit der Japanischen Gesellschaft für Neurochirurgie; 20200621-20200624; sine loco [digital]; DOCV269 /20200626/
Accession number :: edsair.doi.dedup.....051d507d526d82ab8405c9de8169423a
Full Text :: https://doi.org/10.3205/20dgnc265

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