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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 朱士維 | zh_TW |
dc.contributor.advisor | Shi-Wei Chu | en |
dc.contributor.author | 張庭禎 | zh_TW |
dc.contributor.author | Ting-Chen Chang | en |
dc.date.accessioned | 2024-08-05T16:30:08Z | - |
dc.date.available | 2024-08-06 | - |
dc.date.copyright | 2024-08-05 | - |
dc.date.issued | 2024 | - |
dc.date.submitted | 2024-07-26 | - |
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dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/93548 | - |
dc.description.abstract | 大腦由許多互相連接的神經元組成,是多數動物掌管情緒、決策、思考及記憶的重要器官。雖然在現今有關相鄰神經元之訊號傳遞的知識已經有好的發展,但對於神經的湧現性如何使大腦運作的認知仍有限,其中一個最主要的原因來自於大腦體積影像的速度受限。探測大腦中神經元之間的連接與互動需要細胞等級的空間解析度、幾百微米的視野範圍和毫秒等級的時間解析度,為了達到這些條件,我們已經發展了結合多焦距和超高速軸向掃描的雙光子螢光顯微術,體積速度可以達到 543 Hz,並使用 80 MHz 的脈衝雷射當作激發光源。然而,超高體積速度下的權衡即是激發的螢光光子數,為了增加雙光子激發的螢光訊號,我們使用 8 MHz 的脈衝雷射當作新的激發光源,使能量集中在更少的脈衝上。在功率測試中,8 MHz 脈衝雷射只需要約 15 % 的總功率即能達到和 80 MHz 脈衝雷射相當的脈衝激發強度,只要約47 % 的總功率即能達到和80 MHz脈衝雷射相當的激發光子數。
為了使系統能夠採用這兩種雷射光,我們設計了相對應的資料擷取模組。系統最大的資料流能達到 3.20 GB/s,使資料丟失的缺陷容易發生。為了穩定連續的資料流,現場可程式化邏輯閘陣列 (FPGA) 卡扮演了資料流減量的關鍵決策,而在隨機存取記憶體 (RAM) 的平行佇列緩衝則更進一步減少資料丟失的可能。有了高速資料擷取模組,高速雷射掃描系統可以連續存取 400 MB/s 的資料流達 150 秒,800 MB/s 的資料流達 10 至 20 秒,提供了未來探測活體神經之湧現性的潛力。 | zh_TW |
dc.description.abstract | Brain is an important organ that handles emotion, decision, thinking, and memory in most kinds of animals, and it is composed of numerous connected neurons. Nowadays, although the knowledge of how signal transport between adjacent neurons has been developed well, how the brain works from the emergent properties of neurons is still limited. One major obstacle is from the restricted speed of volumetric image inside the brain. To probe the connections and interactions among neurons in the brain, we need cellular spatial resolution, sub-millimeter field of view, and millisecond temporal resolution. To meet these requirements, we have developed two-photon fluorescence microscopy combining multi-beam scanning as well as ultrafast axial scanning technique that leads to a 543 Hz volume rate, and take 80 MHz pulsed laser as the stimulation light. However, the tradeoff of the exceptionally high volume rate is fluorescence photon budget. For the purpose of enhancing the fluorescent signal intensity in two-photon stimulation, we adapted an 8 MHz pulsed laser as the new stimulation beam to concentrate the energy in fewer laser pulses. In the power test, compared with the 80 MHz pulsed laser, the 8 MHz pulsed laser only requires ~15.0 % total power to reach the same intensity in each stimulation, and only requires ~47.0 % total power to reach the same emission photon budget.
In order to enable both laser sources in our system, the corresponding data acquisition module is designed. The maximum dataflow of the system exceeds 3.20 GB/s, which makes the artifact of data loss easily arisen. To stabilize the continuous dataflow, in the data acquisition module, field programmable gate array (FPGA) cards play an important role in the dataflow scale reduction, and the parallel queue buffer in random access memory (RAM) helps to further reduce the probability of data loss. With the high-speed data acquisition module, the high-speed laser scanning system is able to continuously acquire data for 150 seconds when data storage speed is 400 MB/s and 10~20 seconds when data storage speed is 800 MB/s, which gives the potential of probing the emergent properties of living neurons in the future. | en |
dc.description.provenance | Submitted by admin ntu (admin@lib.ntu.edu.tw) on 2024-08-05T16:30:07Z No. of bitstreams: 0 | en |
dc.description.provenance | Made available in DSpace on 2024-08-05T16:30:08Z (GMT). No. of bitstreams: 0 | en |
dc.description.tableofcontents | 口試委員會審定書 i
謝辭 ii 摘要 iv Abstract v Contents vii Figure list x Table list xiii Chapter 1. Introduction: High-speed data processing in neuroscience 1 1.1 Exploring the dynamic responses of neurons 1 1.1.1 The neuron network inside brain 1 1.1.2 Techniques of probing the brain 3 1.1.3 The speed of brain optical imaging 5 1.2 High-speed data processing 8 1.2.1 Data throughput in brain imaging 8 1.2.2 Techniques of high-speed data processing 10 1.3 Aim: Optimize a high-speed data processing system to the two-photon volumetric imaging system with millisecond temporal resolution 13 Chapter 2. Principles: Data processing in two-photon microscopy with ms-scale volume rate 14 2.1 Optical method to achieve imaging with ms-scale volume rate 14 2.1.1 Two-photon stimulation 14 2.1.2 Diffractive optical elements (DOE) 16 2.1.3 Tunable acoustic gradient index of refraction lens (TAG lens) 18 2.1.4 Photomultiplier Tube (PMT) 19 2.2 Hardware to implement data processing with ms-scale volume rate 21 2.2.1 I/O device: Instrument control and data acquisition 21 2.2.2 Computer structures and performances 22 2.2.3 Field programmable gate array (FPGA) 24 2.2.4 PLL frequency multiplier 25 2.3 Data structures and algorithms in high-speed data processing 25 2.3.1 Queue data structures and operations 25 2.3.2 Bitwise operations 27 Chapter 3. System configuration 28 3.1 Optical setup 28 3.1.1 Beam path in the system 28 3.1.2 The position and motion of beam spots 29 3.1.3 Laser source 31 3.1.4 Laser scanning and imaging parameters 34 3.2 High-speed data acquisition module 37 3.2.1 Overview of high-speed data acquisition module 37 3.2.2 Signal synchronization and acquisition 38 3.2.3 Data acquisition hardwares 41 Chapter 4. Data processing from acquisition to reconstruction 46 4.1 FPGA calculation 46 4.1.1 Data from digitizers 47 4.1.2 Downsampling and packaging 48 4.2 Buffer in RAM 50 4.2.1 Data loss causes image shift 50 4.2.2 Quantify data loss 51 4.2.3 Data loss treatment: Queue data structure and data flow adjustment 54 4.3 Image reconstruction 57 4.3.1 From file to volume 57 4.3.2 Image calibration 59 Chapter 5. Image demonstration 65 5.1 Image comparison on lasers in different repetition rate 65 5.1.1 2 MHz laser & 80 MHz laser: Power comparison 65 5.1.2 8 MHz & 80 MHz pulsed laser: Power comparison 67 5.1.3 8 MHz & 80 MHz pulsed laser: Noise comparison 70 5.2 Volumetric images on mouse brain samples 71 Chapter 6. Discussion 74 6.1 The high-speed data processing module 74 6.2 The noise of images 76 6.3 The scanning path 79 Chapter 7. Conclusion and outlook 81 Appendix 82 A. Single-channel scanning 82 B. 16-channel data acquisition software 83 C. Image reconstruction software 86 References 88 | - |
dc.language.iso | en | - |
dc.title | 具有毫秒體積時間解析度的多焦點雙光子螢光顯微鏡之高速數據處理 | zh_TW |
dc.title | High-speed data processing in multifocal two-photon fluorescence microscopy with ms volumetric temporal resolution | en |
dc.type | Thesis | - |
dc.date.schoolyear | 112-2 | - |
dc.description.degree | 碩士 | - |
dc.contributor.oralexamcommittee | 謝佳龍;楊尚達;李夢麟 | zh_TW |
dc.contributor.oralexamcommittee | Chia-Lung Hsieh;Shang-Da Yang;Meng-Lin Li | en |
dc.subject.keyword | 高速資料處理,高速體積影像,雙光子雷射掃描顯微術, | zh_TW |
dc.subject.keyword | High-speed data processing,High-speed volumetric imaging,Two-photon laser scanning microscopy, | en |
dc.relation.page | 94 | - |
dc.identifier.doi | 10.6342/NTU202402065 | - |
dc.rights.note | 同意授權(全球公開) | - |
dc.date.accepted | 2024-07-29 | - |
dc.contributor.author-college | 理學院 | - |
dc.contributor.author-dept | 物理學系 | - |
顯示於系所單位: | 物理學系 |
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