Please use this identifier to cite or link to this item:
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/99338Full metadata record
| ???org.dspace.app.webui.jsptag.ItemTag.dcfield??? | Value | Language |
|---|---|---|
| dc.contributor.advisor | 劉浩澧 | zh_TW |
| dc.contributor.advisor | Hao-Li Liu | en |
| dc.contributor.author | 李永瀚 | zh_TW |
| dc.contributor.author | Yung-Han Lee | en |
| dc.date.accessioned | 2025-09-01T16:08:32Z | - |
| dc.date.available | 2025-09-02 | - |
| dc.date.copyright | 2025-09-01 | - |
| dc.date.issued | 2024 | - |
| dc.date.submitted | 2025-08-08 | - |
| dc.identifier.citation | [1] T. L. Szabo, Diagnostic ultrasound imaging: inside out, Academic Press, 2004.
[2] J. Bercoff, “Ultrafast ultrasound imaging,” Ultrasound Imaging – Medical Applications, pp. 3–24, 2011. [3] M. Cikes et al., “Ultrafast Cardiac Ultrasound Imaging,” JACC: Cardiovascular Imaging, vol. 7, no. 8, pp. 812–823, 2014. [4] A. Ramalli et al., “Real-Time High-Frame-Rate Cardiac B-Mode and Tissue Doppler Imaging Based on Multiline Transmission and Multiline Acquisition,” IEEE Trans. Ultrason. Ferroelectr. Freq. Control, vol. 65, no. 11, pp. 2030–2041, 2018. [5] D. Fischerova, “Ultrasound scanning of the pelvis and abdomen for staging of gynecological tumors: a review,” Ultrasound Obstet. Gynecol., vol. 38, no. 3, pp. 246–266, 2011. [6] H. R. Torres et al., “A review of image processing methods for fetal head and brain analysis in ultrasound images,” Comput. Methods Programs Biomed., vol. 215, p. 106629, 2022. [7] S. Pillen and N. van Alfen, “Skeletal muscle ultrasound,” Neurol. Res., vol. 33, no. 10, pp. 1016–1024, 2011. [8] O. Villemain et al., “Ultrafast Ultrasound Imaging in Pediatric and Adult Cardiology,” JACC: Cardiovasc. Imaging, vol. 13, no. 8, pp. 1771–1791, 2020. [9] M. Couade et al., “Ultrafast imaging of the heart using circular wave synthetic imaging with phased arrays,” in Proc. IEEE Int. Ultrason. Symp., 2009. [10] M. Tanter and M. Fink, “Ultrafast imaging in biomedical ultrasound,” IEEE Trans. Ultrason. Ferroelectr. Freq. Control, vol. 61, no. 1, pp. 102–119, 2014. [11] L. Sandrin et al., “Time-Resolved Pulsed Elastography with Ultrafast Ultrasonic Imaging,” Ultrason. Imaging, vol. 21, no. 4, pp. 259–272, 1999. [12] G. Montaldo et al., “Coherent plane-wave compounding for very high frame rate ultrasonography and transient elastography,” IEEE Trans. Ultrason. Ferroelectr. Freq. Control, vol. 56, no. 3, pp. 489–506, 2009. [13] M. Tanter et al., “Ultrafast compound imaging for 2-D motion vector estimation: application to transient elastography,” IEEE Trans. Ultrason. Ferroelectr. Freq. Control, vol. 49, no. 10, pp. 1363–1374, 2002. [14] S. K. Jespersen, J. E. Wilhjelm, and H. Sillesen, “Multi-Angle Compound Imaging,” Ultrason. Imaging, vol. 20, no. 2, pp. 81–102, 1998. [15] J. A. Jensen et al., “Synthetic aperture ultrasound imaging,” Ultrasonics, vol. 44, pp. e5–e15, 2006. [16] S. Yan et al., “Ultrafast ultrasound vector doppler for small vasculature imaging,” IEEE Trans. Ultrason. Ferroelectr. Freq. Control, vol. 70, no. 7, pp. 613–624, 2023. [17] B. Beliard et al., “Ultrafast doppler imaging and ultrasound localization microscopy reveal the complexity of vascular rearrangement in chronic spinal lesion,” Sci. Rep., vol. 12, p. 6574, 2022. [18] S. L. Norman et al., “Functional ultrasound imaging of deep visual cortex in awake nonhuman primates reveals reliable correlation with local neural activity,” Nat. Commun., vol. 13, p. 1222, 2022. [19] A. Dizeux et al., “Functional ultrasound imaging of the brain reveals propagation of task-related brain activity in behaving primates,” Nat. Commun., vol. 10, p. 1400, 2019. [20] É. Macé et al., “Functional ultrasound imaging of the brain,” Nat. Methods, vol. 8, no. 8, pp. 662–664, 2011. [21] G. Pinton, J.-F. Aubry, E. Bossy, M. Muller, M. Pernot, and M. Tanter, “Attenuation, scattering, and absorption of ultrasound in the skull bone,” Med. Phys., vol. 39, no. 1, pp. 299–307, 2011. [22] K. Shapoori et al., “An ultrasonic-adaptive beamforming method and its application for trans skull imaging of certain types of head injuries (Part I: Transmission mode),” IEEE Trans. Biomed. Eng., vol. 62, no. 5, pp. 1253–1264, 2015. [23] C. Errico et al., “Transcranial functional ultrasound imaging of the brain using MBs-enhanced ultrasensitive Doppler,” NeuroImage, vol. 124, no. Pt A, pp. 752–761, 2016. [24] C. Aurup et al., “Transcranial functional ultrasound imaging detects focused ultrasound neuromodulation induced hemodynamic changes in mouse and nonhuman primate brains in vivo,” bioRxiv, 2024. [25] E. Betzig et al., “Imaging intracellular fluorescent proteins at nanometer resolution,” Science, vol. 313, no. 5793, pp. 1642–1645, 2006. [26] M. J. Rust, M. Bates, and X. Zhuang, “Sub-diffraction-limit imaging by stochastic optical reconstruction microscopy (STORM),” Nat. Methods, vol. 3, no. 10, pp. 793–796, 2006. [27] B. Huang, H. Babcock, and X. Zhuang, “Breaking the diffraction barrier: super-resolution imaging of cells,” Cell, vol. 143, no. 7, pp. 1047–1058, 2010. [28] H. Deschout et al., “Precisely and accurately localizing single emitters in fluorescence microscopy,” Nat. Methods, vol. 11, no. 3, pp. 253–266, 2014. [29] O. Couture et al., “Ultrasound Localization Microscopy and Super-Resolution: A State of the Art,” IEEE Trans. Ultrason. Ferroelectr. Freq. Control, vol. 65, no. 8, pp. 1304–1320, 2018. [30] O. M. Viessmann et al., “Acoustic super-resolution with ultrasound and MBs,” Phys. Med. Biol., vol. 58, no. 18, pp. 6447–6458, 2013. [31] B. Cox and P. Beard, “Super-resolution ultrasound,” Nature, vol. 527, no. 7579, pp. 451–452, 2015. [32] K. Christensen-Jeffries et al., “Super resolution ultrasound imaging,” Ultrasound Med. Biol., vol. 46, no. 4, pp. 865–891, 2020. [33] Y. Desailly, J. Pierre, O. Couture, and M. Tanter, “Resolution limits of ultrafast ultrasound localization microscopy,” Phys. Med. Biol., vol. 60, no. 22, pp. 8723–8740, 2015. [34] C. Errico et al., “Ultrafast ultrasound localization microscopy for deep super-resolution vascular imaging,” Nature, vol. 527, no. 7579, pp. 499–502, 2015. [35] K. Christensen-Jeffries et al., “In Vivo Acoustic Super Resolution and Super Resolved Velocity Mapping Using MBs,” IEEE Trans. Med. Imaging, vol. 34, no. 2, pp. 433–440, 2015. [36] J. Foiret et al., “Ultrasound localization microscopy to image and assess microvasculature in a rat kidney,” Sci. Rep., vol. 7, p. 13662, 2017. [37] Q. Chen et al., “Ultrasound super resolution imaging provides a noninvasive assessment of renal microvasculature changes during mouse acute kidney injury,” Kidney Int., vol. 98, no. 2, pp. 355–365, 2020. [38] F. Lin et al., “3D Ultrasound Localization Microscopy for Identifying Microvascular Morphology Features of Tumor Angiogenesis,” Theranostics, vol. 7, no. 1, pp. 196–204, 2017. [39] J. Zhu et al., “3D Super Resolution US Imaging of Rabbit Lymph Node Vasculature In Vivo by Using MBs,” Radiology, vol. 291, no. 3, pp. 642–650, 2019. [40] O. Demeulenaere et al., “Functional ultrasound imaging in behaving and resting states,” 2022. [41] R. J. van Sloun et al., “Super resolution ultrasound localization microscopy through deep learning,” arXiv preprint arXiv:1801.01088, 2018. [42] A. Renaudin et al., “Transcranial functional ultrasound imaging in freely moving awake mice and anesthetized newborns using a wearable probe,” eBioMedicine, vol. 83, p. 104192, 2022. [43] C. Demené et al., “Transcranial ultrafast ultrasound localization microscopy of brain vasculature in patients,” Nat. Biomed. Eng., vol. 5, pp. 219–228, 2021. [44] L. S. Vidyaratne and K. M. Iftekharuddin, “Real-time epileptic seizure detection using EEG,” IEEE Trans. Neural Syst. Rehabil. Eng., vol. 25, no. 11, pp. 2146–2156, 2017. [45] R. S. Fisher et al., “Epileptic seizures and epilepsy: Definitions proposed by the ILAE and the IBE,” Epilepsia, vol. 46, no. 4, pp. 470–472, 2005. [46] T. A. Fountas et al., “Post mortem dissections of the Papez circuit and nonmotor targets for functional neurosurgery,” World Neurosurg., vol. 144, pp. e866–e875, 2020. [47] K. L. Dell, M. J. Cook, and M. I. Maturana, “Deep brain stimulation for epilepsy: Biomarkers for optimization,” Curr. Treat. Options Neurol., vol. 21, p. 47, 2019. [48] J. Engel Jr., “Introduction to temporal lobe epilepsy,” Epilepsy Res., vol. 26, no. 1, pp. 141–150, 1996. [49] W. J. Tyler, “Noninvasive neuromodulation with ultrasound? A continuum mechanics hypothesis,” Neuroscientist, vol. 17, no. 1, pp. 25–36, 2011. [50] A. Fomenko et al., “Low-intensity ultrasound neuromodulation: An overview of mechanisms and emerging human applications,” Brain Stimul., vol. 11, no. 6, pp. 1209–1217, 2018. [51] J. Kubanek et al., “Ultrasound modulates ion channel currents,” Sci. Rep., vol. 6, p. 24170, 2016. [52] P. P. Ye, J. R. Brown, and K. B. Pauly, “Frequency dependence of ultrasound neurostimulation in the mouse brain,” Ultrasound Med. Biol., vol. 44, no. 12, pp. 2679–2692, 2018. [53] O. Naor, S. Krupa, and S. Shoham, “Ultrasonic neuromodulation,” J. Neural Eng., vol. 13, no. 3, p. 031003, 2016. [54] S.-G. Chen et al., “Transcranial focused ultrasound pulsation suppresses pentylenetetrazol induced epilepsy in vivo,” Brain Stimul., vol. 12, no. 6, pp. 1365–1374, 2019. [55] J. L. Sanguinetti et al., “Transcranial focused ultrasound to the right prefrontal cortex improves mood and alters functional connectivity in humans,” Brain Stimul., vol. 13, no. 1, pp. 173–180, 2020. [56] B. K. Min et al., “Focused ultrasound-mediated suppression of chemically-induced acute epileptic EEG activity,” BMC Neurosci., vol. 12, p. 23, 2011. [57] J. Blackmore et al., “Ultrasound neuromodulation: A review of results, mechanisms and safety,” Ultrasound Med. Biol., vol. 45, no. 7, pp. 1509–1536, 2019. [58] P.-C. Chu et al., “Pulsed-focused ultrasound provides long-term suppression of epileptiform bursts in the kainic acid-induced epilepsy rat model,” Neurotherapeutics, vol. 19, no. 4, pp. 1368–1380, 2022. [59] H. Yang et al., “Closed-loop transcranial ultrasound stimulation for real-time non-invasive neuromodulation in vivo,” Front. Neurosci., vol. 14, p. 445, 2020. [60] R. F. Dallapiazza et al., “Noninvasive neuromodulation and thalamic mapping with low-intensity focused ultrasound,” J. Neurosurg., vol. 128, no. 3, pp. 875–884, 2018. [61] T. Shimada and K. Yamagata, “Pentylenetetrazole-induced kindling mouse model,” J. Vis. Exp., no. 136, p. e57769, 2018. [62] A. Dhir, “Pentylenetetrazol (PTZ) kindling model of epilepsy,” Curr. Protoc. Neurosci., ch. 9, unit 9.37, 2012. [63] R. Q. Huang et al., “Pentylenetetrazole-induced inhibition of recombinant γ-aminobutyric acid type A (GABA<sub>A</sub>) receptors: mechanism and site of action,” J. Pharmacol. Exp. Ther., vol. 298, no. 3, pp. 986–995, 2001. [64] R. L. Macdonald and J. L. Barker, “Pentylenetetrazol and penicillin are selective antagonists of GABA-mediated post-synaptic inhibition in cultured mammalian neurones,” Nature, vol. 267, no. 5608, pp. 720–721, 1977. [65] S. Panwar and S. Gupta, “Comparing different doses of pentylenetetrazole induced experimental model of seizure in mice,” Int. J. Pharm. Sci. Res., vol. 15, no. 10, pp. 3010–3018, 2024. [66] A. Lüttjohann, P. F. Fabene, and G. van Luijtelaar, “A revised Racine's scale for PTZ-induced seizures in rats,” Physiol. Behav., vol. 98, no. 5, pp. 579–587, 2009. [67] W. Löscher, “Critical review of current animal models of seizures and epilepsy used in the discovery and development of new antiepileptic drugs,” Seizure, vol. 20, no. 5, pp. 359–368, 2011. [68] E. S. Yuen and I. F. Trocóniz, “Can pentylenetetrazole and maximal electroshock rodent seizure models quantitatively predict antiepileptic efficacy in humans?” Seizure, vol. 24, pp. 21–27, 2015. [69] S. N. Mandhane, K. Aavula, and T. Rajamannar, “Timed pentylenetetrazol infusion test: a comparative analysis with s.c. PTZ and MES models of anticonvulsant screening in mice,” Seizure, vol. 16, no. 7, pp. 636–640, 2007. [70] M. E. Brevard et al., “Imaging the neural substrates involved in the genesis of pentylenetetrazol-induced seizures,” Epilepsia, vol. 47, no. 4, pp. 745–754, 2006. [71] A. M. Airaksinen et al., “Imaging of pentylenetetrazol-induced seizures by fMRI,” in Proc. ISMRM, vol. 20, p. 371, 2012. [72] B. P. Keogh et al., “BOLD-fMRI of PTZ-induced seizures in rats,” Epilepsy Res., vol. 66, no. 1–3, pp. 75–90, 2005. [73] B. Wang, J. Xiao, and H. Jiang, “Simultaneous real-time 3D photoacoustic tomography and EEG for neurovascular coupling study in an animal model of epilepsy,” J. Neural Eng., vol. 11, no. 4, p. 046013, 2014. [74] J. Provost et al., “3D ultrafast ultrasound imaging in vivo,” IEEE Trans. Med. Imaging, vol. 37, no. 6, pp. 1497–1507, 2018. [75] Jérôme et al., “Adaptive Spatiotemporal SVD Clutter Filtering for Ultrafast Doppler Imaging Using Similarity of Spatial Singular Vectors,” IEEE Trans. Ultrason. Ferroelectr. Freq. Control, vol. 65, no. 11, pp. 1857–1868, 2018. [76] “SonoVue,” [Online]. Available: https://www.mims.com/singapore/drug/info/sonovue?type=full | - |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/99338 | - |
| dc.description.abstract | 中樞神經系統的超音波影像技術可用於觀察腦部血流變化，但受限於穿透顱骨所需之低頻訊號，其影像品質常受到顱骨衰減、視野範圍與空間解析度的限制。超音波定位顯微成像透過優化微氣泡訊號，可突破繞射極限、提升成像解析度，惟現有實驗多使用高頻超音波，限制其經顱應用的可行性。本研究提出一套低頻率超音波定位顯微成像方法，用以偵測並調控戊四氮誘發之癲癇模型中血管動態的變化。我們使用一具500 kHz、64通道、球面聚焦之線性陣列換能器，並以Prodigy系統驅動進行平面波影像資料擷取。透過五角度複合式平面波發射（-15°至15°），提升了影像的訊噪比。實驗中透過靜脈注射MBs增強血管對比度，並以腹腔注射PTZ誘發癲癇發作。同一支換能器亦用於發送低頻聚焦超音波，以進行癲癇抑制之神經調控。影像處理方面，採用奇異值分解技術分離組織與血管訊號，並藉由理論點擴散函數進行互相關濾波，以濾除低信賴度之MBs訊號。低階SVD成分用以定義組織運動，高階成分則反映腦部血流動態。在體外交叉管實驗中，證實500 kHz球面換能器可精確定位MBs，並實現橫向解析度突破繞射極限。在體內實驗中，傳統500 kHz之B-mode影像對大鼠腦部解剖結構顯示有限，而ULM技術則成功提供高解析之皮質血管影像。癲癇大鼠顯示出明顯增加之MBs檢測數與血管訊號亮度，相較於對照組，顯示癲癇期間腦部灌流量上升。進一步施以低頻FUS治療後，癲癇大鼠的血管活動與MBs數量明顯下降，顯示其具備有效抑制癲癇的潛力。本研究所建構之雙模態系統，具備同一平台下即時監測與介入腦部疾病的潛能。總結而言，本研究驗證了低頻率ULM可行於經顱成像與非侵入式神經調控，未來有望作為功能性腦部成像與超音波癲癇治療的新興工具。 | zh_TW |
| dc.description.abstract | Ultrasound imaging in central nervous system enables observing cerebral blood flow variation, but is mostly limited by the skull attenuation, field of view, and spatial resolution due to low frequencies required for penetrating the skull. With the implementation of Ultrasound Localization Microscopy (ULM), imaging resolution can overcome the diffraction limit by optimizing the microbubble (MBs) signals, but experiment mostly relies on high-frequency ultrasound, restricting its transcranial applicability.
In this study, we propose a low-frequency ULM approach for detecting and modulating seizure-induced vascular changes in a rat model of pentylenetetrazol induced epilepsy. A 500 kHz, 64-channel, spherically focused linear array transducer was driven by the Prodigy system to acquire plane-wave image data. Five-angle compounded plane-wave transmissions (-15° to 15°) improved signal-to-noise ratio (SNR). MBs were administered intravenously to enhance vascular contrast, while seizures were induced via intraperitoneal injection of PTZ. In addition to imaging, the same transducer was used to deliver low-frequency focused ultrasound (FUS) for seizure suppression. Singular Value Decomposition (SVD) was applied to separate tissue and vascular signals. A cross-correlation filter using a theoretical point spread function further suppressed low-confidence MBS signals. Low-rank SVD components were used for tissue motion defining, while high-rank components captured cerebral hemodynamics. Results from the in vitro cross-tube experiment confirmed the feasibility of accurate MBs localization and lateral resolution beyond the diffraction limit with the 500 kHz spherical transducer. In vivo, conventional 500kHz B-mode imaging provided limited anatomical detail of rat brain, whereas ULM enabled high-resolution visualization of cortical vasculature. Epileptic rats exhibited significantly increased MBs detection counts and brighter vascular signals compared to sham controls, indicating elevated cerebral perfusion during seizures. Epileptic rats were then received low-frequency FUS, reduced the vascular activity and MBs count relative to untreated epilepsy rats, suggesting a successful suppression effect. This dual-mode capability highlights the potential for real-time brain disorder monitoring and intervention with the same hardware platform. In conclusion, this study demonstrates the feasibility of low-frequency theranostic ultrasound for transcranial ULM imaging and noninvasive neuromodulation. The proposed system offers a promising tool for both functional brain imaging and ultrasound-based seizure therapy. | en |
| dc.description.provenance | Submitted by admin ntu (admin@lib.ntu.edu.tw) on 2025-09-01T16:08:32Z No. of bitstreams: 0 | en |
| dc.description.provenance | Made available in DSpace on 2025-09-01T16:08:32Z (GMT). No. of bitstreams: 0 | en |
| dc.description.tableofcontents | Acknowledgement i
中文摘要 ii Abstract iii Table Of Contents v List Of Figures viii Chapter 1. Introduction 1 1.1 Ultrasound Imaging 1 1.1.1 Conventional Ultrasound Imaging 1 1.1.2 Coherent Planewave Compound Imaging 1 1.2 Functional Ultrasound 3 1.2.1 Limitations in Transcranial Applications 4 1.3 Ultrasound Localization Microscopy 4 1.3.1 Applications in ULM 5 1.4 Overview of Epilepsy and Seizure Mechanisms 8 1.4.1 Epidemiology 8 1.4.2 Pentylenetetrazol as a seizure model 9 1.5 Ultrasound Neuromodulation and Epilepsy Intervention 10 1.6 Research Motivation and Objectives 11 Chapter 2. Material and Method 13 2.1 Experimental Overview 13 2.2 Transducer Sequence Control 13 2.3 Ultrasound Image Construction 14 2.3.1 Plane Wave Compounding and Beamforming 15 2.4 Low Frequency Ultrasound Localization Microscopy Workflow 17 2.4.1 ULM Processing Pipeline 17 2.4.2 Singular Value Decomposition Filtering 18 2.4.3 Spatial Linear Interpolation 22 2.4.4 Cross-Correlation Image Processing and Background Noise Suppression 24 2.4.5 Peak Localization 25 2.5 In Vitro Experiments 26 2.5.1 Cross-Tube Phantom Validation Experiment 26 2.5.2 Image Resolution Characterization 27 2.6 In Vivo Experiment 29 2.6.1 Animal Preparation and Positioning 29 2.6.2 Experimental Procedure 32 2.7 Ultrasound System 34 2.7.1 64-channel Spherical 1-D Array Transducer 34 2.7.2 S-sharp Prodigy 35 2.7.3 External Power Supply 36 2.8 MBs 37 2.9 Sound Field and Acoustic Intensity Measurement 37 2.9.1 Measurement Setup and Hydrophone Configuration 37 2.9.2 Spatial Scanning and Sound Pressure Calibration 38 2.10 Evaluation Metrics 39 Chapter 3. Experimental Result 40 3.1 Acoustic and Imaging Performance 40 3.1.1 Acoustic Calibration and Pressure Field Mapping 40 3.1.2 Image Resolution Evaluation 44 3.2 In Vitro Validation: Cross Tube Flow Phantom 45 3.3 In Vivo Low Frequency ULM Application in Rat Model 48 3.3.1 Baseline Vascular Dynamics in PD and ULM 49 3.3.2 Vasculature ROI vs. Tissue ROI 53 3.3.3 Cerebral Blood Flow in Normal vs. Epileptic Conditions 54 3.3.4 FUS Neuromodulation Effects on Epileptic Brain 57 Chapter 4. Discussion 59 4.1 MBs Detection and Spatial Resolution Constraints 59 4.2 Tissue Motion and Cerebrovascular Dynamics across SVD Orders 59 4.3 Frame Input Duration: 4.5 Minutes vs. 18 Minutes 60 Chapter 5. Conclusion and Future Work 63 Reference 65 | - |
| dc.language.iso | en | - |
| dc.subject | 功能性超音波 | zh_TW |
| dc.subject | 診療合一 | zh_TW |
| dc.subject | 血管成像 | zh_TW |
| dc.subject | 超音波定位顯微術 | zh_TW |
| dc.subject | 經顱超音波 | zh_TW |
| dc.subject | 超音波神經調控 | zh_TW |
| dc.subject | Vasculature Imaging | en |
| dc.subject | Functional Ultrasound | en |
| dc.subject | Theranostic | en |
| dc.subject | Ultrasound localization microscopy | en |
| dc.subject | Ultrasound neuro-modulation | en |
| dc.subject | Transcranial ultrasound | en |
| dc.title | 低頻超音波定位顯微成像用於偵測戊四氮誘發之癲癇發作 | zh_TW |
| dc.title | Low-Frequency Ultrasound Localization Microscopy to Detect Pentylenetetrazol-Induced Epileptic Seizure Onset | en |
| dc.type | Thesis | - |
| dc.date.schoolyear | 113-2 | - |
| dc.description.degree | 碩士 | - |
| dc.contributor.oralexamcommittee | 葉秩光;謝寶育;謝宗勳 | zh_TW |
| dc.contributor.oralexamcommittee | Chih-Kuang Yeh;Bao-Yu Hsieh;Tsung-Hsun Hsieh | en |
| dc.subject.keyword | 經顱超音波,血管成像,超音波定位顯微術,超音波神經調控,功能性超音波,診療合一, | zh_TW |
| dc.subject.keyword | Transcranial ultrasound,Vasculature Imaging,Ultrasound localization microscopy,Ultrasound neuro-modulation,Functional Ultrasound,Theranostic, | en |
| dc.relation.page | 71 | - |
| dc.identifier.doi | 10.6342/NTU202503900 | - |
| dc.rights.note | 同意授權(全球公開) | - |
| dc.date.accepted | 2025-08-12 | - |
| dc.contributor.author-college | 工學院 | - |
| dc.contributor.author-dept | 醫學工程學系 | - |
| dc.date.embargo-lift | 2030-08-05 | - |
| Appears in Collections: | 醫學工程學研究所 | |
Files in This Item:
| File | Size | Format | |
|---|---|---|---|
| ntu-113-2.pdf Until 2030-08-05 | 5.42 MB | Adobe PDF |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.