Dual segmentation models for poorly and well-differentiated hepatocellular carcinoma using two-step transfer deep learning on dynamic contrast-enhanced CT images

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Dual segmentation models for poorly and well-differentiated hepatocellular carcinoma using two-step transfer deep learning on dynamic contrast-enhanced CT images

Persistent ID (NDL): info:ndljp/pid/13734030

Material type: 博士論文

Author: 永見, 範幸

Publisher: 永見, 範幸

Publication date: 2023

Material Format: Digital

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Name of awarding university/degree: 九州大学,博士(保健学)

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Material Type: 博士論文
Title: Dual segmentation models for poorly and well-differentiated hepatocellular carcinoma using two-step transfer deep learning on dynamic contrast-enhanced CT images
Author/Editor: 永見, 範幸
Publication, Distribution, etc.: 永見, 範幸
Publication Date: 2023
Publication Date (W3CDTF): 2023
Alternative Title: ダイナミック造影CT画像における2段階転移深層学習を用いた低・高分化肝細胞がんのデュアルセグメンテーションモデル
Degree grantor/type: 九州大学
Date Granted: 2023-03-20
Date Granted (W3CDTF): 2023-03-20
Dissertation Number: 甲第16464号
Degree Type: 博士(保健学)
Text Language Code: eng
Alias of Author: Nagami, Noriyuki
DOI: 10.1007/s13246-022-01202-7
https://doi.org/10.1007/s13246-022-01202-7
Persistent ID (NDL): info:ndljp/pid/13734030
https://dl.ndl.go.jp/pid/13734030
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Collection (Materials For Handicapped People:1): テキストデータ
Collection (particular): 国立国会図書館デジタルコレクション > デジタル化資料 > 博士論文
https://dl.ndl.go.jp/collections/A00014
Acquisition Basis: 博士論文（送信）
Date Accepted (W3CDTF): 2024-08-16T13:27:53+09:00
Format (IMT): application/pdf
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