Relevant bibliographies by topics / 3D brain imaging

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic '3D brain imaging'

Author: Grafiati
Published: 7 July 2024
Last updated: 31 July 2025

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Journal articles on the topic "3D brain imaging"

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Sumithra, M., P. Madhumitha, S. Madhumitha, D. Malini, and B. Poorni Vinayaa. "3D Segmentation of Brain Tumor Imaging." International Journal of Advanced Engineering, Management and Science 6, no. 6 (2020): 256–60. http://dx.doi.org/10.22161/ijaems.66.5.

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Kakeda, Shingo, Yukunori Korogi, Yasuhiro Hiai, Norihiro Ohnari, Toru Sato, and Toshinori Hirai. "Pitfalls of 3D FLAIR Brain Imaging." Academic Radiology 19, no. 10 (2012): 1225–32. http://dx.doi.org/10.1016/j.acra.2012.04.017.

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Taranda, Julian, and Sevin Turcan. "3D Whole-Brain Imaging Approaches to Study Brain Tumors." Cancers 13, no. 8 (2021): 1897. http://dx.doi.org/10.3390/cancers13081897.

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Although our understanding of the two-dimensional state of brain tumors has greatly expanded, relatively little is known about their spatial structures. The interactions between tumor cells and the tumor microenvironment (TME) occur in a three-dimensional (3D) space. This volumetric distribution is important for elucidating tumor biology and predicting and monitoring response to therapy. While static 2D imaging modalities have been critical to our understanding of these tumors, studies using 3D imaging modalities are needed to understand how malignant cells co-opt the host brain. Here we summa
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Yao, Junjie. "Deep-brain imaging with 3D integrated photoacoustic tomography and ultrasound localization microscopy." Journal of the Acoustical Society of America 155, no. 3_Supplement (2024): A53. http://dx.doi.org/10.1121/10.0026774.

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Photoacoustic computed tomography (PACT) is a proven technology for imaging hemodynamics in deep brain of small animal models. PACT is inherently compatible with ultrasound (US) imaging, providing complementary contrast mechanisms. While PACT can quantify the brain’s oxygen saturation of hemoglobin (sO2), US imaging can probe the blood flow based on the Doppler effect. Furthermore, by tracking gas-filled microbubbles, ultrasound localization microscopy (ULM) can map the blood flow velocity with sub-diffraction spatial resolution. In this work, we present a 3D deep-brain imaging system that sea
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Pooh, Ritsuko K. "Three-dimensional Evaluation of the Fetal Brain." Donald School Journal of Ultrasound in Obstetrics and Gynecology 11, no. 4 (2017): 268–75. http://dx.doi.org/10.5005/jp-journals-10009-1532.

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ABSTRACT Three-dimensional (3D) ultrasound is one of the most attractive modalities in the field of fetal ultrasound imaging. Combination of both transvaginal sonography and 3D ultrasound may be a great diagnostic tool for evaluation of 3D structure of fetal central nervous system (CNS). Recent advanced 3D ultrasound equipments have several useful functions, such as surface anatomy imaging; multiplanar imaging of the intracranial structure; tomographic ultrasound imaging of fetal brain in the any cutting section; bony structural imaging of the calvaria and vertebrae; thick slice imaging of the
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Ren, Jiahao, Xiaocen Wang, Chang Liu, et al. "3D Ultrasonic Brain Imaging with Deep Learning Based on Fully Convolutional Networks." Sensors 23, no. 19 (2023): 8341. http://dx.doi.org/10.3390/s23198341.

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Compared to magnetic resonance imaging (MRI) and X-ray computed tomography (CT), ultrasound imaging is safer, faster, and more widely applicable. However, the use of conventional ultrasound in transcranial brain imaging for adults is predominantly hindered by the high acoustic impedance contrast between the skull and soft tissue. This study introduces a 3D AI algorithm, Brain Imaging Full Convolution Network (BIFCN), combining waveform modeling and deep learning for precise brain ultrasound reconstruction. We constructed a network comprising one input layer, four convolution layers, and one po
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Avasarala, Jagannadha, and Todd Pietila. "The first 3D printed multiple sclerosis brain: Towards a 3D era in medicine." F1000Research 6 (August 30, 2017): 1603. http://dx.doi.org/10.12688/f1000research.12336.1.

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Conventional magnetic resonance imaging (MRI) studies depict disease of the human brain in 2D but the reconstruction of a patient’s brain stricken with multiple sclerosis (MS) in 3D using 2D images has not been attempted. Using 3D reconstruction algorithms, we built a 3D printed patient-specific brain model to scale. It is a first of its kind model that depicts the total white matter lesion (WML) load using T2 FLAIR images in an MS patient. The patient images in Digital Imaging and Communications in Medicine (DICOM) format were imported into Mimics inPrint 2.0 (Materialise NV, Leuven, Belgium)
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Avasarala, Jagannadha, and Todd Pietila. "The first 3D printed multiple sclerosis brain: Towards a 3D era in medicine." F1000Research 6 (September 20, 2017): 1603. http://dx.doi.org/10.12688/f1000research.12336.2.

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Conventional magnetic resonance imaging (MRI) studies depict disease of the human brain in 2D but the reconstruction of a patient’s brain stricken with multiple sclerosis (MS) in 3D using 2D images has not been attempted. Using 3D reconstruction algorithms, we built a 3D printed patient-specific brain model to scale. It is a first of its kind model that depicts the total white matter lesion (WML) load using T2 FLAIR images in an MS patient. The patient images in Digital Imaging and Communications in Medicine (DICOM) format were imported into Mimics inPrint 2.0 (Materialise NV, Leuven, Belgium)
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Miao, Peng, Zhixia Wu, Miao Li, et al. "Synchrotron Radiation X-Ray Phase-Contrast Tomography Visualizes Microvasculature Changes in Mice Brains after Ischemic Injury." Neural Plasticity 2016 (2016): 1–8. http://dx.doi.org/10.1155/2016/3258494.

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Imaging brain microvasculature is important in plasticity studies of cerebrovascular diseases. Applying contrast agents, traditionalμCT andμMRI methods gain imaging contrast for vasculature. The aim of this study is to develop a synchrotron radiation X-ray inline phase-contrast tomography (SRXPCT) method for imaging the intact mouse brain (micro)vasculature in high resolution (~3.7 μm) without contrast agent. A specific preparation protocol was proposed to enhance the phase contrast of brain vasculature by using density difference over gas-tissue interface. The CT imaging system was developed
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Wang, Hao, Qingyuan Zhu, Lufeng Ding, et al. "Scalable volumetric imaging for ultrahigh-speed brain mapping at synaptic resolution." National Science Review 6, no. 5 (2019): 982–92. http://dx.doi.org/10.1093/nsr/nwz053.

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Abstract The speed of high-resolution optical imaging has been a rate-limiting factor for meso-scale mapping of brain structures and functional circuits, which is of fundamental importance for neuroscience research. Here, we describe a new microscopy method of Volumetric Imaging with Synchronized on-the-fly-scan and Readout (VISoR) for high-throughput, high-quality brain mapping. Combining synchronized scanning beam illumination and oblique imaging over cleared tissue sections in smooth motion, the VISoR system effectively eliminates motion blur to obtain undistorted images. By continuously im
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Dissertations / Theses on the topic "3D brain imaging"

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Matias, Correia T. M. "Assessment and optimisation of 3D optical topography for brain imaging." Thesis, University College London (University of London), 2010. http://discovery.ucl.ac.uk/19496/.

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Optical topography has recently evolved into a widespread research tool for non-invasively mapping blood flow and oxygenation changes in the adult and infant cortex. The work described in this thesis has focused on assessing the potential and limitations of this imaging technique, and developing means of obtaining images which are less artefactual and more quantitatively accurate. Due to the diffusive nature of biological tissue, the image reconstruction is an ill-posed problem, and typically under-determined, due to the limited number of optodes (sources and detectors). The problem must be re
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Law, Kwok-wai Albert, and 羅國偉. "3D reconstruction of coronary artery and brain tumor from 2D medical images." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2004. http://hub.hku.hk/bib/B31245572.

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Uthama, Ashish. "3D spherical harmonic invariant features for sensitive and robust quantitative shape and function analysis in brain MRI." Thesis, University of British Columbia, 2007. http://hdl.handle.net/2429/438.

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A novel framework for quantitative analysis of shape and function in magnetic resonance imaging (MRI) of the brain is proposed. First, an efficient method to compute invariant spherical harmonics (SPHARM) based feature representation for real valued 3D functions was developed. This method addressed previous limitations of obtaining unique feature representations using a radial transform. The scale, rotation and translation invariance of these features enables direct comparisons across subjects. This eliminates need for spatial normalization or manually placed landmarks required in most convent
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Olivero, Daniel. "Traumatic brain injury biomarker discovery using mass spectrometry imaging of 3D neural cultures." Thesis, Georgia Institute of Technology, 2011. http://hdl.handle.net/1853/41102.

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Biomarker research is of great interest in the field of traumatic brain injury (TBI), since there are numerous potential markers that may indicate central nervous system damage, yet the brain is normally well isolated and discovery is at its infancy. Traditional methods for biomarker discovery include time consuming multi step chromatographic mass spectrometery (MS) techniques or pre-defined serial probing using traditional assays, making the identification of biomarker panels limiting and expensive. These shortfalls have motivated the development of a MS based probe that can be embedded into
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MomayyezSiahkal, Parya. "3D stochastic completion fields for mapping brain connectivity using diffusion magnetic resonance imaging." Thesis, McGill University, 2012. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=110445.

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This thesis proposes a novel probabilistic method for measuring anatomical connectivity in the brain based on measurements obtained from diffusion magnetic resonance imaging. We approach the problem of fibre tractography from the viewpoint that a computational theory should relate to the underlying quantity that is being measured--the anisotropic diffusion of water molecules in fibrous tissues. To achieve this goal, the prior probability of completion between two particular regions of interest is modelled by a 3D directional random walk, which is representative of the ensemble anisotropic disp
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Collins, D. Louis. "3D model-based segmentation of individual brain structures from magnetic resonance imaging data." Thesis, McGill University, 1994. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=28716.

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This thesis addresses a specific problem of model-based segmentation; namely, the automatic identification and delineation of gross anatomical structures of the human brain based on their appearance in magnetic resonance images (MRI). The approach developed in this thesis depends on a general, iterative, hierarchical registration procedure and a 3-D digital model of human brain anatomy that contains both volumetric intensity-based data and geometric atlas data that co-exist in a brain-based stereotaxic coordinate system. The model contains features derived from an MRI atlas of gross neuroanato
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Christopoulos, Charitos Andreas. "Brain disease classification using multi-channel 3D convolutional neural networks." Thesis, Linköpings universitet, Statistik och maskininlärning, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-174329.

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Functional magnetic resonance imaging (fMRI) technology has been used in the investigation of human brain functionality and assist in brain disease diagnosis. While fMRI can be used to model both spatial and temporal brain functionality, the analysis of the fMRI images and the discovery of patterns for certain brain diseases is still a challenging task in medical imaging. Deep learning has been used more and more in medical field in an effort to further improve disease diagnosis due to its effectiveness in discovering high-level features in images. Convolutional neural networks (CNNs) is a cla
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Mayerich, David Matthew. "Acquisition and reconstruction of brain tissue using knife-edge scanning microscopy." Texas A&M University, 2003. http://hdl.handle.net/1969.1/563.

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A fast method for gathering large-scale data sets through the serial sectioning of brain tissue is described. These data sets are retrieved using knife-edge scanning microscopy, a new technique developed in the Brain Networks Laboratory at Texas A&M University. This technique allows the imaging of tissue as it is cut by an ultramicrotome. In this thesis the development of a knife-edge scanner is discussed as well as the scanning techniques used to retrieve high-resolution data sets. Problems in knife-edge scanning microscopy, such as illumination, knife chatter, and focusing are discussed. Tec
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Heinzer, Stefan. "Hierarchical 3D imaging and quantification of brain microvasculature in a mouse model for Alzheimer's disease /." Zürich : ETH, 2007. http://e-collection.ethbib.ethz.ch/show?type=diss&nr=17293.

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Nguyen, Peter. "CANNABINOID RECEPTORS IN THE 3D RECONSTRUCTED MOUSE BRAIN: FUNCTION AND REGULATION." VCU Scholars Compass, 2010. http://scholarscompass.vcu.edu/etd/2274.

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CB1 receptors (CB1R) mediate the psychoactive and therapeutic effects of cannabinoids including ∆9-tetrahydrocannabinol (THC), the main psychoactive constituent in marijuana. However, therapeutic use is limited by side effects and tolerance and dependence with chronic administration. Tolerance to cannabinoid-mediated effects is associated with CB1R adaptations, including desensitization (receptor-G-protein uncoupling) and downregulation (receptor degradation). The objectives of this thesis are to investigate the regional-specificity in CB1R function and regulation. Previous studies have invest
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Books on the topic "3D brain imaging"

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Kretschmann, Hans-Joachim. Neurofunctional systems: 3D reconstructions with correlated neuroimaging. Thieme, 1998.

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1957-, Lucerna S., ed. In vivo atlas of deep brain structures: With 3D reconstructions. Springer, 2002.

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Naidich, Thomas P. Duvernoy’s Atlas of the Human Brain Stem and Cerebellum: High-Field MRI: Surface Anatomy, Internal Structure, Vascularization and 3D Sectional Anatomy. Springer Vienna, 2009.

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Kumazawa-Manita, Noriko, Tsutomu Hashikawa, and Atsushi Iriki. The 3D Stereotaxic Brain Atlas of the Degu: With MRI and Histology Digital Model with a Freely Rotatable Viewer. Springer, 2018.

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Kumazawa-Manita, Noriko, Tsutomu Hashikawa, and Atsushi Iriki. The 3D Stereotaxic Brain Atlas of the Degu: With MRI and Histology Digital Model with a Freely Rotatable Viewer. Springer, 2019.

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Harder, B., T. Hagemann, Martin C. Hirsch, Thomas Kramer, and C. Zinecker. Neuroanatomy: 3D-Stereoscopic Atlas of the Human Brain. Springer London, Limited, 2012.

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Salpietro, F. M., S. Lucerna, C. Alafaci, and F. Tomasello. In Vivo Atlas of Deep Brain Structures: With 3D Reconstructions. Springer Berlin / Heidelberg, 2012.

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Salpietro, F. M., S. Lucerna, C. Alafaci, and F. Tomasello. In Vivo Atlas of Deep Brain Structures: With 3D Reconstructions. Springer London, Limited, 2012.

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Hirsch, Martin C., and Thomas Kramer. Neuroanatomy: 3D-Stereoscopic Atlas of the Human Brain (With CD-ROM). Springer, 1999.

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Heinzer, Stefan. Hierarchical 3D imaging and quantification of brain microvasculature in a mouse model for Alzheimer's disease. 2007.

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Book chapters on the topic "3D brain imaging"

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Kikinis, Ron, Ferenc A. Jolesz, Guido Gerig, et al. "3D Morphometric and Morphologic Information Derived From Clinical Brain MR Images." In 3D Imaging in Medicine. Springer Berlin Heidelberg, 1990. http://dx.doi.org/10.1007/978-3-642-84211-5_28.

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Song, Zigen, Melinda Baxter, Mingwu Jin, et al. "Sparse Sampling and Fully-3D Fast Total Variation Based Imaging Reconstruction for Chemical Shift Imaging in Magnetic Resonance Spectroscopy." In Brain Informatics. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-05587-5_45.

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Herrmannsdörfer, Frank, Benjamin Flottmann, Siddarth Nanguneri, et al. "3D d STORM Imaging of Fixed Brain Tissue." In Methods in Molecular Biology. Springer New York, 2016. http://dx.doi.org/10.1007/978-1-4939-6688-2_13.

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Wu, Biao, Yutong Xie, Zeyu Zhang, et al. "BHSD: A 3D Multi-class Brain Hemorrhage Segmentation Dataset." In Machine Learning in Medical Imaging. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-45673-2_15.

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Tudosiu, Petru-Daniel, Walter Hugo Lopez Pinaya, Mark S. Graham, et al. "Morphology-Preserving Autoregressive 3D Generative Modelling of the Brain." In Simulation and Synthesis in Medical Imaging. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-16980-9_7.

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Petrov, Dmitry, Boris A. Gutman, Egor Kuznetsov, et al. "Deep Learning for Quality Control of Subcortical Brain 3D Shape Models." In Shape in Medical Imaging. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-04747-4_25.

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Yaqub, Mohammad, Remi Cuingnet, Raffaele Napolitano, et al. "Volumetric Segmentation of Key Fetal Brain Structures in 3D Ultrasound." In Machine Learning in Medical Imaging. Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-02267-3_4.

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Fidon, Lucas, Michael Aertsen, Nada Mufti, et al. "Distributionally Robust Segmentation of Abnormal Fetal Brain 3D MRI." In Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Perinatal Imaging, Placental and Preterm Image Analysis. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-87735-4_25.

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Fang, Longwei, Lichi Zhang, Dong Nie, et al. "Brain Image Labeling Using Multi-atlas Guided 3D Fully Convolutional Networks." In Patch-Based Techniques in Medical Imaging. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-67434-6_2.

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Rusak, Filip, Rodrigo Santa Cruz, Pierrick Bourgeat, et al. "3D Brain MRI GAN-Based Synthesis Conditioned on Partial Volume Maps." In Simulation and Synthesis in Medical Imaging. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-59520-3_2.

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Conference papers on the topic "3D brain imaging"

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Kitching, John. "Chip-Scale Atomic Devices: From Clocks to Brain Imaging and Beyond." In 3D Image Acquisition and Display: Technology, Perception and Applications. Optica Publishing Group, 2024. https://doi.org/10.1364/3d.2024.jw2a.2.

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Chip-scale atomic clocks and sensors combine elements of precision atomic spectroscopy, silicon micromachining and photonics technology to achieve good performance with small size and low power consumption. Recent advances will be discussed including compact optical clocks, micromachined atomic beam clocks. Full-text article not available; see video presentation
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Yao, Jiachen, Nina Hagemann, Qiaojie Xiong, Jianxu Chen, Dirk M. Hermann, and Chao Chen. "Topological Analysis of Mouse Brain Vasculature via 3d Light-Sheet Microscopy Images." In 2024 IEEE International Symposium on Biomedical Imaging (ISBI). IEEE, 2024. http://dx.doi.org/10.1109/isbi56570.2024.10635226.

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Guo, Maotao, Ye Zhou, Siyuan Tang, and Xianglong Li. "Explainable Multimodal Framework for Brain Imaging with 3D MRI and Age Data." In 2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2024. https://doi.org/10.1109/bibm62325.2024.10822478.

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Saladi, S., P. Pinnamaneni, and J. Meyer. "Texture-based 3D brain imaging." In Proceedings 2nd Annual IEEE International Symposium on Bioinformatics and Bioengineering (BIBE 2001). IEEE, 2001. http://dx.doi.org/10.1109/bibe.2001.974422.

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Xiao, Sheng, Hua-an Tseng, Howard Gritton, Xue Han, and Jerome Mertz. "Video-rate Volumetric Neuronal Imaging Using 3D Targeted Illumination." In Optics and the Brain. OSA, 2018. http://dx.doi.org/10.1364/brain.2018.bw2c.6.

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Xue, Yujia, Ian G. Davison, David A. Boas, and Lei Tian. "Computational Miniature Mesoscope for Single-shot 3D Fluorescence Imaging." In Optics and the Brain. OSA, 2020. http://dx.doi.org/10.1364/brain.2020.btu2c.5.

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Loncaric, Sven, Ivan Ceskovic, Ratimir Petrovic, and Srecko Loncaric. "3D quantitative analysis of brain SPECT images." In Medical Imaging 2001, edited by Milan Sonka and Kenneth M. Hanson. SPIE, 2001. http://dx.doi.org/10.1117/12.431055.

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Szalay, Gergely, Zoltán Szadai, Linda Judák, et al. "Fast 3D imaging and photostimulation by 3D acousto-optical microscopy revealed spatiotemporally orchestrated clusters in the visual cortex." In Optics and the Brain. OSA, 2019. http://dx.doi.org/10.1364/brain.2019.bm3a.1.

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Rózsa, Balázs, Zoltán Szadai, Linda Judák, et al. "Imaging of dendrites and sparse interneuronal networks with 3D random access microscopy." In Optics and the Brain. Optica Publishing Group, 2023. http://dx.doi.org/10.1364/brain.2023.bw3b.6.

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Acousto-optical microscopy is a powerful tool to study spare networks and extensive dendritic arborization from the cortex of behaving animals. We used this novel approach for imaging dendrites and somata of sparse interneuron populations in a combination with auditory discrimination and detection tasks. Our results shed light of not yet known subcellular and network mechanisms from multiple brain regions.
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Li, Wenze, Venkatakaushik Voleti, Evan Schaffer, et al. "SCAPE Microscopy for High Speed, 3D Whole-Brain Imaging in Drosophila Melanogaster." In Optics and the Brain. OSA, 2016. http://dx.doi.org/10.1364/brain.2016.btu4d.3.

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