Fine-Tuning Approach for Segmentation of Gliomas in Brain Magnetic Resonance Images with a Machine Learning Method to Normalize Image Differences among Facilities

SIMPLE SUMMARY: This study evaluates the performance degradation of machine learning models for segmenting gliomas in brain magnetic resonance images caused by domain shift and proposed possible solutions. Although machine learning models exhibit significant potential for clinical applications, perf...

Πλήρης περιγραφή

Αποθηκεύτηκε σε:
Λεπτομέρειες βιβλιογραφικής εγγραφής
Τόπος έκδοσης:Cancers (Basel)
Κύριοι συγγραφείς: Takahashi, Satoshi, Takahashi, Masamichi, Kinoshita, Manabu, Miyake, Mototaka, Kawaguchi, Risa, Shinojima, Naoki, Mukasa, Akitake, Saito, Kuniaki, Nagane, Motoo, Otani, Ryohei, Higuchi, Fumi, Tanaka, Shota, Hata, Nobuhiro, Tamura, Kaoru, Tateishi, Kensuke, Nishikawa, Ryo, Arita, Hideyuki, Nonaka, Masahiro, Uda, Takehiro, Fukai, Junya, Okita, Yoshiko, Tsuyuguchi, Naohiro, Kanemura, Yonehiro, Kobayashi, Kazuma, Sese, Jun, Ichimura, Koichi, Narita, Yoshitaka, Hamamoto, Ryuji
Μορφή: Artigo
Γλώσσα:Inglês
Έκδοση: MDPI 2021
Θέματα:
Article
Διαθέσιμο Online:https://ncbi.nlm.nih.gov/pmc/articles/PMC8003655/
https://ncbi.nlm.nih.gov/pubmed/33808802
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/cancers13061415
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