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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 魏安祺(An-Chi Wei) | |
| dc.contributor.author | Chi-Jung Huang | en |
| dc.contributor.author | 黃麒戎 | zh_TW |
| dc.date.accessioned | 2022-11-24T03:23:18Z | - |
| dc.date.available | 2025-02-11 | |
| dc.date.available | 2022-11-24T03:23:18Z | - |
| dc.date.copyright | 2022-02-21 | |
| dc.date.issued | 2022 | |
| dc.date.submitted | 2022-02-09 | |
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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/80950 | - |
| dc.description.abstract | 細胞在生長過程中可分為四個階段，屬於間期的G1、S、G2以及分裂期 (M)，不同階段的細胞除了外型變化外，內部的胞器如細胞核、粒腺體型態也會隨生長有所不同。要觀察細胞週期常用的方法為流式細胞術，其可以分析螢光強度判斷細胞位在哪個週期。現今的流式細胞儀也可進行影像拍攝，但其缺點為儀器拍攝時放大倍率及影像解析度不足，無法輕易分辨細胞較細小的胞器。在本篇論文中，我們利用fluorescence ubiquitination-based cell cycle indicator (FUCCI)及MitoTrackerTM對AC16心肌細胞的細胞週期及粒線體標定，並使用能拍出高倍率及高解析度影像的雷射共軛焦顯微鏡來拍攝時間序列上細胞變化的影像。得到的細胞穿透光及螢光影像則用於分類細胞位於哪一週期階段。在拍攝細胞影像時，為避免使用過多雷射通道造成的光毒性問題，我們不直接標定細胞核，而是利用U-net對細胞核螢光影像進行預測。最後我們將預測出的細胞核影像與拍攝的顯微鏡影像一同放入卷積神經網路ResNet及MobilenetV2訓練預測細胞位於哪個週期階段，在精確度上相比只放入螢光及穿透光影像有所提升。整體而言使用預測的螢光影像即可幫助提高分類週期的準確性，這個方法可以降低事前準備螢光染色的時間，更能讓觀察顏色有限的螢光顯微技術多了彈性調整的空間，讓研究者能觀察其他胞器在不同週期中的變化。 | zh_TW |
| dc.description.provenance | Made available in DSpace on 2022-11-24T03:23:18Z (GMT). No. of bitstreams: 1 U0001-0402202220543500.pdf: 2852626 bytes, checksum: eb25908876eb9422c310c8e278276b42 (MD5) Previous issue date: 2022 | en |
| dc.description.tableofcontents | Acknowledgment ………………………………………………………… i 摘要 ……………………………………………………………………… ii Abstract ……………………………………………………………… iii Table of Contents ………………………………………………………… v List of Figures …………………………………………………… vii List of Tables …………………………………………………………… ix Chapter I: Introduction ..………………………………………………… 1 Section 1-1: Background and Motivation ……………………………… 1 Section 1-2: Literature Review ………………………………………… 7 Section 1-3: Significance ……………………………………………… 18 Chapter II: Methods and Materials …………………………………… 20 Section 2-1: Cell Culture and Cell Staining …………………………… 20 Section 2-2: Image Acquisition ………………………………………… 21 Section 2-3: Data Preprocessing ……………………………………… 24 Section 2-4: Model Training …………………………………………… 32 Chapter III: Results ……………………………………………………… 40 Section 3-1: Prediction from Bright-field Images ……………………… 40 Section 3-2: FUCCI Vector (RFP) Classification ……………………… 42 Section 3-3: FUCCI BacMan2.0 (GFP) Classification ………………… 44 Section 3-4: FUCCI Vector (GFP) Classification ……………………… 45 Section 3-5: FUCCI Vector (RFP GFP) Classification ……………… 47 Section 3-6 Classification with predicted mitochondria ……………… 50 Chapter IV: Discussion ………………………………………………… 53 Section 4-1 Results Analysis …………………………………………… 53 Section 4-2 Other Analysis …………………………………………… 54 Section 4-3 Experiment Difficulties and Limitation …………………… 59 Section 4-4 Potential Application ……………………………………… 60 Chapter V: Conclusion and Future Work ………………………………… 61 Reference ……………………………………………………………… 63 | |
| dc.language.iso | en | |
| dc.subject | 螢光影像預測 | zh_TW |
| dc.subject | U-net | zh_TW |
| dc.subject | ResNet | zh_TW |
| dc.subject | MobilenetV2 | zh_TW |
| dc.subject | 細胞週期 | zh_TW |
| dc.subject | FUCCI | zh_TW |
| dc.subject | MobilenetV2 | en |
| dc.subject | Cell Cycle | en |
| dc.subject | FUCCI | en |
| dc.subject | Prediction of Fluorescence Image | en |
| dc.subject | U-net | en |
| dc.subject | ResNet | en |
| dc.title | 根據粒線體及細胞核顯微影像利用深度學習分類細胞週期 | zh_TW |
| dc.title | Deep-Learning Classification of Cell Cycle Phases Based on Mitochondrial and Nucleus Microscopic Images | en |
| dc.date.schoolyear | 110-1 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 劉彥良(Yu-Shao Chen),何亦平(Chia-Ying Chiang),(Chia-Chang Lin) | |
| dc.subject.keyword | 細胞週期,FUCCI,螢光影像預測,U-net,ResNet,MobilenetV2, | zh_TW |
| dc.subject.keyword | Cell Cycle,FUCCI,Prediction of Fluorescence Image,U-net,ResNet,MobilenetV2, | en |
| dc.relation.page | 69 | |
| dc.identifier.doi | 10.6342/NTU202200281 | |
| dc.rights.note | 同意授權(限校園內公開) | |
| dc.date.accepted | 2022-02-10 | |
| dc.contributor.author-college | 電機資訊學院 | zh_TW |
| dc.contributor.author-dept | 生醫電子與資訊學研究所 | zh_TW |
| dc.date.embargo-lift | 2025-02-11 | - |
| 顯示於系所單位： | 生醫電子與資訊學研究所 | |
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