臺灣博碩士論文加值系統

了解大腦是如何運作的對於腦神經科學家而言是最重要的研究目標之一。近幾年來，神經科學家們相信大腦內部的神經連結是使大腦形成功能的最基礎單元，而這些神經連結被稱為connectome。了解這些連結是如何傳遞訊號、和形成功能性神經網路可以幫助我們了解許多重要的問題，包含記憶是如何產生的，為什麼人類會有意識等等。
然而，要了解功能性神經網路並非一件簡單的事。在神經網路中，每一個神經元都有著複雜的三維結構，而神經元的大小都只有僅僅數微米大，且神經事件的產生都只有僅僅數毫秒的時間。此外，神經訊號的量測必須為非侵入式以避免環境改變而造成神經訊號的傳遞改變。因此，發展一個同時能夠記錄三維神經訊號、非侵入式且同時具有高空間解析度及時間解析度的工具有著高度的重要性。
在現有的技術中，光學顯微鏡是一個最可能符合上述條件的技術。光學顯微鏡是一個非侵入性的成像方法，能夠提供低於微米等級的解析度能力。此外，光學顯微鏡能夠量測許多神經的功能性反應，例如：鈣離子濃度變化、膜電位的改變等等。然而，光學顯微鏡在三維高解析度的成像速度上仍然有著侷限性，在深組織的成像上，光學顯微鏡必須仰賴雙光子掃描顯微鏡技術達成光學切片效果及減少散射的影響。但也因為雙光子掃描顯微鏡必須先在XY平面上掃描每個點後再慢慢移動物鏡或載物台逐層掃描而降低了光學顯微鏡的成像速率。
這幾年來有不少人提出改進雙光子顯微鏡成像的方法，然而大部分的方法都還是只能提升其中一個軸度的成像速度，使得速度上仍不足以快到跟上神經的傳遞速率。有些團隊成功同時提高了軸向和橫向的成像速度，例如：快速變焦鏡與光片照明顯微鏡的結合，但這類的方法往往依賴廣視野顯微鏡技術的使用，會造成很強的散射，使得在深組織影像中無法使用。
為了加快雙光子掃描顯微鏡的速度，我們自行設計一套多光子多焦點顯微鏡，提升橫向上的成像速率。在軸向上，我們利用了快速變焦透鏡達到快速焦距變化，進而達到高速掃描。這個顯微鏡的組合不僅可以同時提升軸向和橫向的成像速度，另外我們保留了掃描顯微鏡的特性，使得在深組織中至於因為訊號光的散射而不至於導致影像品質的變壞。
除此之外，在這篇論文裡我們也提出一個搭配高速掃描系統的超高速脈衝偵測系統之新設計超高速的光脈衝偵測系統用以提升系統訊雜比。其概念主要為利用光電倍增管對光子的反應具有特定波型和雷射脈衝具有固定週期之特性的以作為過濾雜訊的根據。我們設計了兩種方法：分別為對光電倍增管輸出對特定波型做擬合得出光強度大小之方法及利用time-gated方法，僅在螢光放光其間取值進行訊雜比之提升。
在本研究中，我們成功架設出了快速掃描顯微鏡系統及高速脈衝偵測系統。雖然目前還有一些問題如多焦點造成的串擾問題及偵測系統的雜訊問題，但我們仍然期待這套系統之後可以做為腦神經科學研究的重要工具。

Understanding how the brain functions is a fundamental goal for neuroscientists. Over years of study, neuroscietists belive the neural interconnections insided the brain is the most fundamental thing to function the brain and the connections are are termed “connectomes.” The communication and functional connectivity of these connectomes are called “functional connectomes.” Resolving these functional connectomes can help people understand some essential questions, such as how the memories forms, and why we have consciousness
Nevertheless, functional connectome study is not an easy task. It is because that the neuron networks inside the brain exhibit three-dimensional structures. The spatial size of neuron is small on the order of several micrometer (μm) and the temporal dynamics of neural events is fast with several millisecond (ms) in scale. Besides, the functional neurons can hide deep from the brain surface, requiring the recording method to be not only non-invasive, but also capable of isolating from the environment. Therefore, to study functional connectome, it is necessary to develop tools with capability of three-dimensional recording, non-invasive observation and high spatail and temporal resolution.
Among current techniques, optical microscopy is a promising method to meet those requirements. It can achieve non-invasive detection and provide sub-μm spatial resolution. Besides, optical microscopy is compatible with a variety of functional sensors such as voltage, calcium, or metabolic indicators. Nevertheless, optical microscopy still has its limitation. In deep tissue imaging, conventional wide-field optical microscopy suffers from strong scattering and signal mix-up due to lack of optical sectioning capability. Although two-photon laser scanning microscopy provides significant improvement on these issues, however, the imaging speed is limited. To acquire a 3D volume image, it requires to laterally scan every pixel on XY plane and then scan axially by moving objective lens or sample.
During the past decade, several techniques have been proposed to enhance the imaging speed of two-photon microscopy. However, most of them cannot enhance the imaging speed on lateral and axial direction at the same time, making it still difficult to catch up the neuron signal propogation. Recently some groups have successfully enhance speed on both lateral and axial directions, such as the combination of light-sheet microscopy and a electric tunable lens. However, those techniques are wide-field illumination based and the signal may suffer from scattering.
In this thesis, to improve the slow 3D imaging prbolem, we combine multifocal multiphoton microscopy with a tunable acoustic gradient index of refraction lens to enhance lateral and axial scanning speed simultaneously. This combination can greatly enhance imaging speed as well as reduce the effect of tissue scattering due to its scanning feature.
Furthermore, we design and realize a high speed pulse detection system to improve signal-to-noise ratio, based on the knowledge that the pulse repsonse of photomultiplier tube has a charactertic waveform and the laser pulse repetiton rate is fixed. In our work, we propose two methods: one is signal pulse fitting method that can filter out the noises that doesn’t fit the signal waveform requirements. The other one is time-gated method, which detects signals only within a specific time after each excitation pulse.
By combining the high-speed scanning system with the high-speed detection system, we will be able to detect 3D neuronal dynamics inside brain with very high spatiotemporal resolution. Though currently, our techniques still require to be improved in terms of multiple beams cross-talk and noise influence, we expect this system will be a powerful tool for functional connectome study in the near future.

口試委員會審定書 #
誌謝 I
中文摘要 III
ABSTRACT V
CONTENTS VIII
LIST OF FIGURES XII
Chapter 1 Introduction 3
1.1 Brain and the functional study 3
1.2 Difficulties for functional connectome research 3
1.3 Optical microscopy for brain study 4
1.4 My Aim: Fast 3D and deep tissue optical microscopy 5
1.5 Multifocal multiphoton microscopy with tunable acoustic gradient index of refraction lens 6
1.6 High SNR and fast detection system 6
Chapter 2 Optical microscopy for brain study: with a special emphasis on depth, speed and 3D imaging 8
2.1 Limitation of optical microscopy in brain study 8
2.2 Methods to improve two-photon microscopy imaging rate 9
2.2.1 Fast axial imaging techniques 10
2.2.2 Fast lateral imaging techniques 13
2.2.3 Other techniques 17
2.3 Fast 3D imaging microscopy 17
2.4 More about the TAG lens and its application 19
Chapter 3 Design of fast 3D imaging microscopy 23
3.1 The beam splitting methods for MMM 23
3.2 The scanning methods for MMM 26
3.3 The detection methods for MMM 30
3.4 MMM test by spinning disk scanning units 33
3.4.1 Test sample 34
3.4.2 Steps and results 34
3.4.3 Discussion 37
3.5 The fast 3D MMM design: 38
3.6 The optical light path design 38
3.7 The detection system design 42
3.7.1 Photon counting detection 42
3.7.2 Based on high-speed pulse detection 43
3.7.3 Based on pulse fitting method 44
3.7.4 Based on multi-threshold time-gating method 45
3.7.5 Notification 47
Chapter 4 Construction of the fast 3D imaging microscope 48
4.1 About the optical light path: 48
4.1.1 The beam number 48
4.1.2 The splitting angle of DOE 49
4.2 About the detection system 53
4.2.1 The photo-multiplier tube (PMT) 54
4.2.2 The current to voltage converter and Amplifier 57
4.2.3 The data acquisition (DAQ) 59
4.2.4 The data acquisition: fitting the pulse 62
4.2.5 The data acquisition: time-gated maximum value detection 64
4.3 Other specifications of the detection system 67
4.3.1 Output rate of the DAQ 67
4.3.2 The amplification of amplifier 67
4.4 The combination of the TAG lens and the MMM system 68
Chapter 5 Experiment and results 70
5.1 The simulation of 32 -pixel image of drosophila brain 70
5.2 The optical light path 70
5.2.1 The DOE performance: 70
5.2.2 The constructed setup 71
5.2.3 The two-photon imaging test: 72
5.2.4 Focus extension test: 76
5.3 The amplifier and PMT test: 79
5.3.1 Amplifier test 79
5.3.2 PMT and amplifier test 80
5.4 DAQ test 81
5.4.1 The MVT pulse fitting method： 82
5.4.2 The time-gated maximum value detection method： 83
Chapter 6 Discussion 88
6.1 About the Image blur: 88
6.1.1 Way to improving optical sectioning 89
6.2 About the large noise for detection system problem 91
6.2.1 Estimation of noises from amplifier 91
6.2.2 Way to avoid external noises 93
Chapter 7 Conclusion 96
7.1.1 Optical light path part 96
7.1.2 Detection part 96
7.1.3 Current progress and future work 97
Chapter 8 Appendix 99
8.1 The approximation of collected photon number 99
8.2 Amplification test 102
8.3 PMT with Amplifier test 104
Chapter 9 References 106

1.Pelvig, D.P., et al., Neocortical glial cell numbers in human brains. Neurobiology of Aging, 2008. 29(11): p. 1754-1762.
2.Sporns, O., G. Tononi, and R. Kotter, The Human Connectome: A Structural Description of the Human Brain. PLoS Comput Biol, 2005. 1(4): p. e42.
3.Schrodel, T., et al., Brain-wide 3D imaging of neuronal activity in Caenorhabditis elegans with sculpted light. Nat Meth, 2013. 10(10): p. 1013-1020.
4.Briggman, K.L. and W.B. Kristan, Multifunctional Pattern-Generating Circuits. Annual Review of Neuroscience, 2008. 31(1): p. 271-294.
5.Niessing, J. and R.W. Friedrich, Olfactory pattern classification by discrete neuronal network states. Nature, 2010. 465(7294): p. 47-52.
6.Churchland, M.M., et al., Neural population dynamics during reaching. Nature, 2012. 487(7405): p. 51-56.
7.Megı́as, M., et al., Total number and distribution of inhibitory and excitatory synapses on hippocampal CA1 pyramidal cells. Neuroscience, 2001. 102(3): p. 527-540.
8.Ambros-Ingerson, J. and W.R. Holmes, Analysis and comparison of morphological reconstructions of hippocampal field CA1 pyramidal cells. Hippocampus, 2005. 15(3): p. 302-315.
9.Scanziani, M. and M. Hausser, Electrophysiology in the age of light. Nature, 2009. 461(7266): p. 930-939.
10.Belliveau, J., et al., Functional mapping of the human visual cortex by magnetic resonance imaging. Science, 1991. 254(5032): p. 716-719.
11.Hillman, E.M.C., Optical brain imaging in vivo: techniques and applications from animal to man. Journal of biomedical optics, 2007. 12(5): p. 051402-051402.
12.Raichle, M.E. and M.A. Mintun, BRAIN WORK AND BRAIN IMAGING. Annual Review of Neuroscience, 2006. 29(1): p. 449-476.
13.Wilt, B.A., et al., Advances in Light Microscopy for Neuroscience. Annual review of neuroscience, 2009. 32: p. 435.
14.Jin, L., et al., Single action potentials and subthreshold electrical events imaged in neurons with a novel fluorescent protein voltage probe. Neuron, 2012. 75(5): p. 779-785.
15.Hsu, K.-J., All-in-focus functional imaging system for drosophila brain activities study, in Department of Physics. 2014, National Taiwan University: Taiwan. p. 76.
16.Ahrens, M.B., et al., Whole-brain functional imaging at cellular resolution using light-sheet microscopy. Nat Meth, 2013. 10(5): p. 413-420.
17.Keller, P.J., et al., Reconstruction of Zebrafish Early Embryonic Development by Scanned Light Sheet Microscopy. Science, 2008. 322(5904): p. 1065-1069.
18.Kim, K.H., C. Buehler, and P.T.C. So, High-speed, two-photon scanning microscope. Applied Optics, 1999. 38(28): p. 6004-6009.
19.Lee, A.M.D., et al., In vivo video rate multiphoton microscopy imaging of human skin. Optics Letters, 2011. 36(15): p. 2865-2867.
20.Lechleiter, J.D., D.-T. Lin, and I. Sieneart, Multi-photon laser scanning microscopy using an acoustic optical deflector. Biophysical Journal, 2002. 83(4): p. 2292-2299.
21.Callamaras, N. and I. Parker, Construction of a confocal microscope for real-time x-y and x-z imaging. Cell Calcium, 1999. 26(6): p. 271-279.
22.Stan, C.A., Liquid optics: Oscillating lenses focus fast. Nat Photon, 2008. 2(10): p. 595-596.
23.Hung-Chun Lin, M.-S.C., and Yi-Hsin Lin, A Review of Electrically Tunable Focusing Liquid Crystal Lenses. TRANSACTIONS ON ELECTRICAL AND ELECTRONIC MATERIALS, 2011. 12(6): p. 9.
24.Mermillod-Blondin, A., E. McLeod, and C.B. Arnold, High-speed varifocal imaging with a tunable acoustic gradient index of refraction lens. Optics Letters, 2008. 33(18): p. 2146-2148.
25.Bewersdorf, J., A. Egner, and S.W. Hell, Multifocal Multi-Photon Microscopy, in Handbook Of Biological Confocal Microscopy, B.J. Pawley, Editor. 2006, Springer US: Boston, MA. p. 550-560.
26.Sheppard, C.J.R., et al., Signal-to-Noise Ratio in Confocal Microscopes, in Handbook Of Biological Confocal Microscopy, B.J. Pawley, Editor. 2006, Springer US: Boston, MA. p. 442-452.
27.Sytsma, et al., Time-gated fluorescence lifetime imaging and microvolume spectroscopy using two-photon excitation. Journal of Microscopy, 1998. 191(1): p. 39-51.
28.Kodama, Y., Time Gating of Chloroplast Autofluorescence Allows Clearer Fluorescence Imaging. PLoS ONE, 2016. 11(3): p. e0152484.
29.Vicidomini, G., et al., STED Nanoscopy with Time-Gated Detection: Theoretical and Experimental Aspects. PLoS ONE, 2013. 8(1): p. e54421.
30.Vicidomini, G., et al., Sharper low-power STED nanoscopy by time gating. Nat Meth, 2011. 8(7): p. 571-573.
31.Svoboda, K. and R. Yasuda, Principles of Two-Photon Excitation Microscopy and Its Applications to Neuroscience. Neuron, 2006. 50(6): p. 823-839.
32.Ntziachristos, V., Going deeper than microscopy: the optical imaging frontier in biology. Nat Meth, 2010. 7(8): p. 603-614.
33.Mertz, J., Optical sectioning microscopy with planar or structured illumination. Nat Meth, 2011. 8(10): p. 811-819.
34.Webb, R.H., Theoretical basis of confocal microscopy, in Methods in Enzymology. 1999, Academic Press. p. 3-20.
35.Callamaras, N. and I. Parker, Construction of a confocal microscope for real-time x-y and x-z imaging. Cell Calcium, 1999. 26: p. 271-279.
36.Kerlin, A.M., et al., Broadly Tuned Response Properties of Diverse Inhibitory Neuron Subtypes in Mouse Visual Cortex. Neuron, 2010. 67(5): p. 858-871.
37.Oku, H., K. Hashimoto, and M. Ishikawa, Variable-focus lens with 1-kHz bandwidth. Optics Express, 2004. 12(10): p. 2138-2149.
38.Gobel, W., B.M. Kampa, and F. Helmchen, Imaging cellular network dynamics in three dimensions using fast 3D laser scanning. Nat Meth, 2007. 4(1): p. 73-79.
39.Oku, H., K. Hashimoto, and M. Ishikawa, Variable-focus lens with 1-kHz bandwidth. Opt. Express, 2004. 12: p. 2138-2149.
40.Fahrbach, F.O., et al., Rapid 3D light-sheet microscopy with a tunable lens. Optics Express, 2013. 21(18): p. 21010-21026.
41.Grewe, B.F., et al., Fast two-layer two-photon imaging of neuronal cell populations using an electrically tunable lens. Biomedical Optics Express, 2011. 2(7): p. 2035-2046.
42.Jabbour, J.M., et al., Optical axial scanning in confocal microscopy using an electrically tunable lens. Biomedical Optics Express, 2014. 5(2): p. 645-652.
43.Olivier, N., et al., Two-photon microscopy with simultaneous standard and extended depth of field using a tunable acoustic gradient-index lens. Optics Letters, 2009. 34(11): p. 1684-1686.
44.Kong, L., et al., Continuous volumetric imaging via an optical phase-locked ultrasound lens. Nat Meth, 2015. 12(8): p. 759-762.
45.Hoover, E.E. and J.A. Squier, Advances in multiphoton microscopy technology. Nat Photon, 2013. 7(2): p. 93-101.
46.Pantazis, P. and W. Supatto, Advances in whole-embryo imaging: a quantitative transition is underway. Nat Rev Mol Cell Biol, 2014. 15(5): p. 327-339.
47.Bouchard, M.B., et al., Swept confocally-aligned planar excitation (SCAPE) microscopy for high-speed volumetric imaging of behaving organisms. Nat Photon, 2015. 9(2): p. 113-119.
48.Bewersdorf, J., R. Pick, and S.W. Hell, Multifocal multiphoton microscopy. Optics Letters, 1998. 23(9): p. 655-657.
49.Watson, B.O., V. Nikolenko, and R. Yuste, Two-Photon Imaging with Diffractive Optical Elements. Frontiers in Neural Circuits, 2009. 3: p. 6.
50.Watson, B.O., et al., Two-photon microscopy with diffractive optical elements and spatial light modulators. Frontiers in Neuroscience, 2010. 4.
51.Bahlmann, K., et al., Multifocal multiphoton microscopy (MMM) at a frame rate beyond 600 Hz. Optics Express, 2007. 15(17): p. 10991-10998.
52.Duemani Reddy, G., et al., Three-dimensional random access multiphoton microscopy for functional imaging of neuronal activity. Nat Neurosci, 2008. 11(6): p. 713-720.
53.Salome, R., Ultrafast random-access scanning in two-photon microscopy using acousto-optic deflectors. J. Neurosci. Methods, 2006. 154: p. 161-174.
54.Grewe, B.F., et al., High-speed in vivo calcium imaging reveals neuronal network activity with near-millisecond precision. Nat Meth, 2010. 7(5): p. 399-405.
55.Dal Maschio, M., et al., Three-dimensional in vivo scanning microscopy with inertia-free focus control. Optics Letters, 2011. 36(17): p. 3503-3505.
56.Jiang, J., et al., Fast 3-D temporal focusing microscopy using an electrically tunable lens. Optics Express, 2015. 23(19): p. 24362-24368.
57.Kim, K.H., et al., Multifocal multiphoton microscopy based on multianode photomultiplier tubes. Optics Express, 2007. 15(18): p. 11658-11678.
58.Duocastella, M., B. Sun, and C.B. Arnold, Simultaneous imaging of multiple focal planes for three-dimensional microscopy using ultra-high-speed adaptive optics. Journal of Biomedical Optics, 2012. 17(5): p. 050505-050505.
59.Nielsen, T., et al., High efficiency beam splitter for multifocal multiphoton microscopy. Journal of Microscopy, 2001. 201(3): p. 368-376.
60.Qu, J., et al., RECENT PROGRESS IN MULTIFOCAL MULTIPHOTON MICROSCOPY. Journal of innovative optical health sciences, 2012. 5(3): p. 10.1142/S1793545812500186.
61.Nikolenko, V., et al., SLM Microscopy: Scanless Two-Photon Imaging and Photostimulation with Spatial Light Modulators. Frontiers in Neural Circuits, 2008. 2: p. 5.
62.Jureller, J.E., H.Y. Kim, and N.F. Scherer, Stochastic scanning multiphoton multifocal microscopy. Optics Express, 2006. 14(8): p. 3406-3414.
63.Wegner, F.V., et al., Fast XYT Imaging of Elementary Calcium Release Events in Muscle With Multifocal Multiphoton Microscopy and Wavelet Denoising and Detection. IEEE Transactions on Medical Imaging, 2007. 26(7): p. 925-934.
64.Kobayashi, M., et al., Second-harmonic-generation microscope with a microlens array scanner. Optics Letters, 2002. 27(15): p. 1324-1326.
65.Shimozawa, T., et al., Improving spinning disk confocal microscopy by preventing pinhole cross-talk for intravital imaging. Proceedings of the National Academy of Sciences, 2013. 110(9): p. 3399-3404.
66.Schulz, O., et al., Resolution doubling in fluorescence microscopy with confocal spinning-disk image scanning microscopy. Proceedings of the National Academy of Sciences, 2013. 110(52): p. 21000-21005.
67.Cha, J.W., et al., Non-descanned multifocal multiphoton microscopy with a multianode photomultiplier tube. AIP Advances, 2015. 5(8): p. 084802.
68.Le Grand, Y., et al., Non-descanned versus descanned epifluorescence collection in two-photon microscopy: Experiments and Monte Carlo simulations. Optics Communications, 2008. 281(21): p. 5480-5486.
69.Graf, R., J. Rietdorf, and T. Zimmermann, Live Cell Spinning Disk Microscopy, in Microscopy Techniques: -/-, J. Rietdorf, Editor. 2005, Springer Berlin Heidelberg: Berlin, Heidelberg. p. 57-75.
70.Takahara, Y., N. Matsuki, and Y. Ikegaya, NIPKOW CONFOCAL IMAGING FROM DEEP BRAIN TISSUES. Journal of Integrative Neuroscience, 2011. 10(01): p. 121-129.
71.Spindler, S.R. and V. Hartenstein, The Drosophila neural lineages: a model system to study brain development and circuitry. Development Genes and Evolution, 2010. 220(1-2): p. 1-10.
72.Jennings, B.H., Drosophila – a versatile model in biology & medicine. Materials Today, 2011. 14(5): p. 190-195.
73.Cha, J.W., et al., Reassignment of Scattered Emission Photons in Multifocal Multiphoton Microscopy. Scientific Reports, 2014. 4: p. 5153.
74.Buehler, C., et al., Single-Photon Counting Multicolor Multiphoton Fluorescence Microscope. Journal of Fluorescence, 2005. 15(1): p. 41-51.
75.Computing, M., Data Acquisition Handbook. 3 ed. A Reference For DAQ And Analog & Digital Signal Conditioning. 2004: Measurement Computing.
76.Kumar, S., et al., Multifocal multiphoton excitation and time correlated single photon counting detection for 3-D fluorescence lifetime imaging. Optics Express, 2007. 15(20): p. 12548-12561.
77.Photonics, H., Photon Counting, in PHOTOMULTIPLIER TUBES
Basics and Applications. 2007.
78.Vinegoni, C., et al., Real-time high dynamic range laser scanning microscopy. Nat Commun, 2016. 7.
79.Driscoll, J.D., et al., Photon counting, censor corrections, and lifetime imaging for improved detection in two-photon microscopy. Journal of Neurophysiology, 2011. 105(6): p. 3106-3113.
80.Becker, W., et al. High-speed FLIM data acquisition by time-correlated single-photon counting. 2004.
81.Carriles, R., et al., Simultaneous multifocal, multiphoton, photon counting microscopy. Optics Express, 2008. 16(14): p. 10364-10371.
82.Benninger, R.K.P., et al., Single-photon-counting detector for increased sensitivity in two-photon laser scanning microscopy. Optics Letters, 2008. 33(24): p. 2895-2897.
83.Qingguo, X., et al., A New Approach for Pulse Processing in Positron Emission Tomography. IEEE Transactions on Nuclear Science, 2005. 52(4): p. 988-995.
84.Striker, G., et al., Photochromicity and Fluorescence Lifetimes of Green Fluorescent Protein. The Journal of Physical Chemistry B, 1999. 103(40): p. 8612-8617.
85.Elson, D.S., et al., Real-time time-domain fluorescence lifetime imaging including single-shot acquisition with a segmented optical image intensifier. New Journal of Physics, 2004. 6(1): p. 180.
86.Gu, L., et al., In vivo time-gated fluorescence imaging with biodegradable luminescent porous silicon nanoparticles. Nat Commun, 2013. 4.
87.Negrean, A. and H.D. Mansvelder, Optimal lens design and use in laser-scanning microscopy. Biomedical Optics Express, 2014. 5(5): p. 1588-1609.
88.Stelzer, E.H.K., The Intermediate Optical System of Laser-Scanning Confocal Microscopes, in Handbook Of Biological Confocal Microscopy, B.J. Pawley, Editor. 2006, Springer US: Boston, MA. p. 207-220.
89.Photonics, H., Photomultiplier Tubes Basics and Applications. 3a ed. 2007.
90.PHOTONICS, H., HOW TO USE PHOTOMULTIPLIER TUBES AND PERIPHERAL CIRCUITS, in PMT handbook. 2007.
91.Shukla, A. and U. Kumar, Positron emission tomography: An overview. Journal of Medical Physics, 2006. 31(1): p. 13-21.
92.Xie, Q., et al., Potentials of Digitally Sampling Scintillation Pulses in Timing Determination in PET. IEEE transactions on nuclear science, 2009. 56(5): p. 2607-2613.
93.Xi, D., et al. A PET detector module using FPGA-only MVT digitizers. in 2013 IEEE Nuclear Science Symposium and Medical Imaging Conference (2013 NSS/MIC). 2013.
94.Xi, D., et al., FPGA-Only MVT Digitizer for TOF PET. IEEE Transactions on Nuclear Science, 2013. 60(5): p. 3253-3261.
95.JOUR, T.-., et al., Real time two-photon absorption microscopy using multi point excitation. Journal of Microscopy Journal of Microscopy, 1998. 192.
96.Egner, A. and S.W. Hell, Time multiplexing and parallelization in multifocal multiphoton microscopy. Journal of the Optical Society of America A, 2000. 17(7): p. 1192-1201.
97.Egner, A., V. Andresen, and S.W. Hell, Comparison of the axial resolution of practical Nipkow-disk confocal fluorescence microscopy with that of multifocal multiphoton microscopy: theory and experiment. Journal of Microscopy, 2002. 206(1): p. 24-32.
98.Kester, W., Op Amp Applications Handbook. 2005, Burlington: Newnes. 97-118.
99.Leach, W.M., On the calculation of noise in multistage amplifiers. IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications, 1995. 42(3): p. 176-178.
100.Philbert, S.T. and K. David, In Vivo Two-Photon Laser Scanning Microscopy with Concurrent Plasma-Mediated Ablation Principles and Hardware Realization, in In Vivo Optical Imaging of Brain Function, Second Edition. 2009, CRC Press. p. 59-115.
101.Drobizhev, M., et al., Two-photon absorption properties of fluorescent proteins. Nat Meth, 2011. 8(5): p. 393-399.
102.Suhling, K., et al., Imaging the Environment of Green Fluorescent Protein. Biophysical Journal, 2002. 83(6): p. 3589-3595.