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Relevant bibliographies by topics / Intrinsic optical signal imaging

Academic literature on the topic 'Intrinsic optical signal imaging'

Author: Grafiati

Published: 10 December 2022

Last updated: 28 January 2023

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Journal articles on the topic "Intrinsic optical signal imaging"

1

Yao, Xin-Cheng. "Intrinsic optical signal imaging of retinal activation." Japanese Journal of Ophthalmology 53, no. 4 (July 2009): 327–33. http://dx.doi.org/10.1007/s10384-009-0685-4.

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Das, Aniruddha. "Task-related Responses in Intrinsic-Signal Optical Imaging." Journal of Vision 15, no. 12 (September 1, 2015): 1415. http://dx.doi.org/10.1167/15.12.1415.

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Heimel, J. Alexander, Robin J. Hartman, Josephine M. Hermans, and Christiaan N. Levelt. "Screening mouse vision with intrinsic signal optical imaging." European Journal of Neuroscience 25, no. 3 (February 16, 2007): 795–804. http://dx.doi.org/10.1111/j.1460-9568.2007.05333.x.

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Ribot, Jérôme, Shigeru Tanaka, Hirokazu Tanaka, and Ayako Ajima. "Online analysis method for intrinsic signal optical imaging." Journal of Neuroscience Methods 153, no. 1 (May 2006): 8–20. http://dx.doi.org/10.1016/j.jneumeth.2005.09.016.

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Ba, Alyssa M., Michael Guiou, Nader Pouratian, Arpitha Muthialu, David E. Rex, Andrew F. Cannestra, James W. Y. Chen, and Arthur W. Toga. "Multiwavelength Optical Intrinsic Signal Imaging of Cortical Spreading Depression." Journal of Neurophysiology 88, no. 5 (November 1, 2002): 2726–35. http://dx.doi.org/10.1152/jn.00729.2001.

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Cortical spreading depression (CSD) is an important disease model for migraine and cerebral ischemia. In this study, we exploit the high temporal and spatial resolution of optical imaging to characterize perfusion-dependent and -independent changes in response to CSD and to investigate the etiology of reflectance changes during CSD. In this experiment, we characterized the optical response to CSD at wavelengths that emphasize perfusion-related changes (610 and 550 nm), and we compared these results with 850 nm and blood volume data. Blood volume changes during CSD were recorded using an intravascular fluorescent dye, Texas Red dextran. We observed triphasic optical signals at 850 and 550 nm characterized by spreading waves of increased, decreased, then increased reflectance (Fig. 1 ) which expanded at a rate of approximately 3–5 mm/min. The signal at 610 nm had a similar initial phase, but the phase 2 response was slightly more complex, with a parenchymal decrease in reflectance but a vascular increase in reflectance. Reflectance values decreased in phase three. Blood volume signals were delayed relative to the optical intrinsic signals and corresponded temporally to phases 2 and 3. This is the first study to characterize optical imaging of intrinsic signal responses to CSD, in vivo, at multiple wavelengths. The data presented here suggest that changes in light scattering precede perfusion responses, the blood volume increase (phase 2) is accompanied by a reduction in deoxyhemoglobin, and the blood volume decrease (phase 3) is accompanied by an increase in deoxyhemoglobin. Previous studies have suggested the oligemia of spreading depression was a result of decreased metabolic demand. This study suggests that during the oligemic period there is a greater reduction in oxygen delivery than in demand.

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Chen, J. W. Y., A. M. O'Farrell, and A. W. Toga. "Optical intrinsic signal imaging in a rodent seizure model." Neurology 55, no. 2 (July 25, 2000): 312–15. http://dx.doi.org/10.1212/wnl.55.2.312.

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Yao, Xincheng, and Benquan Wang. "Intrinsic optical signal imaging of retinal physiology: a review." Journal of Biomedical Optics 20, no. 9 (September 25, 2015): 090901. http://dx.doi.org/10.1117/1.jbo.20.9.090901.

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Guevara, E., M. Miranda-Morales, K. Hernández-Vidales, M. Atzori, and F. J. González. "Low-cost embedded system for optical imaging of intrinsic signals." Revista Mexicana de Física 65, no. 6 Nov-Dec (October 31, 2019): 651. http://dx.doi.org/10.31349/revmexfis.65.651.

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This paper describes the proof-of-concept evaluation of a low-cost imaging system for obtaining functional connectivity maps of in vivo murine models. This non-contact system is based on the Raspberry Pi 3 and its V2 camera and offers a method for obtaining resting-state images of brain activity without the use of extrinsic contrast agents. The system was fully characterized in terms of dark signal, linearity, sensor noise resolution and spatial frequency response. One mouse was observed in vivo and functional connectivity maps were obtained by combining resting-state analysis and optical intrinsic signals imaging. Intra-mouse variations in functional connectivity remain consistent across multiple imaging sessions. In principle, inexpensive optical imaging of intrinsic signals allows the study of the mechanisms underlying human brain disorders in well-controlled murine models.

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YAO, XIN-CHENG, LEI LIU, and YANG-GUO LI. "INTRINSIC OPTICAL SIGNAL IMAGING OF RETINAL ACTIVITY IN FROG EYE." Journal of Innovative Optical Health Sciences 02, no. 02 (April 2009): 201–8. http://dx.doi.org/10.1142/s1793545809000462.

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Using a near-infrared (NIR) light flood-illumination imager equipped with a high-speed (120 Hz) CCD camera, we demonstrated optical imaging of stimulus-evoked retinal activity in isolated, but intact, frog eye. Both fast and slow transient intrinsic optical signals (IOSs) were observed. Fast optical response occurred immediately after the stimulus onset, could reach peak magnitude within 100 ms, and correlated tightly with ON and OFF edges of the visible light stimulus; while slow optical response lasted a relatively long time (many seconds). High-resolution images revealed both positive (increasing) and negative (decreasing) IOSs, and dynamic optical change at individual CCD pixels could often exceed 10% of the background light intensity. Our experiment on isolated eye suggests that further development of fast, high (sub-cellular) resolution fundus imager will allow robust detection of fast IOSs in vivo, and thus allow noninvasive, three-dimensional evaluation of retinal neural function.

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Bakin, Jonathan S., Michael C. Kwon, Susan A. Masino, Norman M. Weinberger, and Ron D. Frostig. "Suprathreshold Auditory Cortex Activation Visualized by Intrinsic Signal Optical Imaging." Cerebral Cortex 6, no. 2 (1996): 120–30. http://dx.doi.org/10.1093/cercor/6.2.120.

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Dissertations / Theses on the topic "Intrinsic optical signal imaging"

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Berwick, Jason. "Investigation of the V-signal oscillation using intrinsic optical imaging and imaging spectroscopy and its relevance to cortical metabolism." Thesis, University of Sheffield, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.312793.

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Harel, Noam. "Functional organization of auditory cortex revealed by optical imaging of intrinsic signals." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape2/PQDD_0025/NQ49983.pdf.

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Labron, Mark William. "Imaging the effects of acute osmotic stress on the rat neocortical slice using intrinsic optical signals and calcein fluorescence." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp01/MQ36047.pdf.

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Xu, Wei. "Analog Signal Processing for Optical Coherence Imaging Systems." Diss., The University of Arizona, 2006. http://hdl.handle.net/10150/195225.

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Optical coherence tomography (OCT) and optical coherence microscopy (OCM) are non-invasive optical coherence imaging techniques, which enable micron-scale resolution, depth resolved imaging capability. Both OCT and OCM are based on Michelson interferometer theory. They are widely used in ophthalmology, gastroenterology and dermatology, because of their high resolution, safety and low cost. OCT creates cross sectional images whereas OCM obtains en face images. In this dissertation, the design and development of three increasingly complicated analog signal processing (ASP) solutions for optical coherence imaging are presented.The first ASP solution was implemented for a time domain OCT system with a Rapid Scanning Optical Delay line (RSOD)-based optical signal modulation and logarithmic amplifier (Log amp) based demodulation. This OCT system can acquire up to 1600 A-scans per second. The measured dynamic range is 106dB at 200A-scan per second. This OCT signal processing electronics includes an off-the-shelf filter box with a Log amp circuit implemented on a PCB board.The second ASP solution was developed for an OCM system with synchronized modulation and demodulation and compensation for interferometer phase drift. This OCM acquired micron-scale resolution, high dynamic range images at acquisition speeds up to 45,000 pixels/second. This OCM ASP solution is fully custom designed on a perforated circuit board.The third ASP solution was implemented on a single 2.2 mm x 2.2 mm complementary metal oxide semiconductor (CMOS) chip. This design is expandable to a multiple channel OCT system. A single on-chip CMOS photodetector and ASP channel was used for coherent demodulation in a time domain OCT system. Cross-sectional images were acquired with a dynamic range of 76dB (limited by photodetector responsivity). When incorporated with a bump-bonded InGaAs photodiode with higher responsivity, the expected dynamic range is close to 100dB.

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Raguet, Hugo. "A Signal Processing Approach to Voltage-Sensitive Dye Optical Imaging." Thesis, Paris 9, 2014. http://www.theses.fr/2014PA090031/document.

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L’imagerie optique par colorant potentiométrique est une méthode d’enregistrement de l’activité corticale prometteuse, mais dont le potentiel réel est limité par la présence d’artefacts et d’interférences dans les acquisitions. À partir de modèles existant dans la littérature, nous proposons un modèle génératif du signal basé sur un mélange additif de composantes, chacune contrainte dans une union d’espaces linéaires déterminés par son origine biophysique. Motivés par le problème de séparation de composantes qui en découle, qui est un problème inverse linéaire sous-déterminé, nous développons : (1) des régularisations convexes structurées spatialement, favorisant en particulier des solutions parcimonieuses ; (2) un nouvel algorithme proximal de premier ordre pour minimiser efficacement la fonctionnelle qui en résulte ; (3) des méthodes statistiques de sélection de paramètre basées sur l’estimateur non biaisé du risque de Stein. Nous étudions ces outils dans un cadre général, et discutons leur utilité pour de nombreux domaines des mathématiques appliqués, en particulier pour les problèmes inverses ou de régression en grande dimension. Nous développons par la suite un logiciel de séparation de composantes en présence de bruit, dans un environnement intégré adapté à l’imagerie optique par colorant potentiométrique. Finalement, nous évaluons ce logiciel sur différentes données, synthétiques et réelles, montrant des résultats encourageants quant à la possibilité d’observer des dynamiques corticales complexes
Voltage-sensitive dye optical imaging is a promising recording modality for the cortical activity, but its practical potential is limited by many artefacts and interferences in the acquisitions. Inspired by existing models in the literature, we propose a generative model of the signal, based on an additive mixtures of components, each one being constrained within an union of linear spaces, determined by its biophysical origin. Motivated by the resulting component separation problem, which is an underdetermined linear inverse problem, we develop: (1) convex, spatially structured regularizations, enforcing in particular sparsity on the solutions; (2) a new rst-order proximal algorithm for minimizing e›ciently the resulting functional; (3) statistical methods for automatic parameters selection, based on Stein’s unbiased risk estimate.We study thosemethods in a general framework, and discuss their potential applications in variouselds of applied mathematics, in particular for large scale inverse problems or regressions. We develop subsequently a soŸware for noisy component separation, in an integrated environment adapted to voltage-sensitive dye optical imaging. Finally, we evaluate this soŸware on dišerent data set, including synthetic and real data, showing encouraging perspectives for the observation of complex cortical dynamics

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R, S. Umesh. "Algorithms for processing polarization-rich optical imaging data." Thesis, Indian Institute of Science, 2004. http://hdl.handle.net/2005/96.

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This work mainly focuses on signal processing issues related to continuous-wave, polarization-based direct imaging schemes. Here, we present a mathematical framework to analyze the performance of the Polarization Difference Imaging (PDI) and Polarization Modulation Imaging (PMI). We have considered three visualization parameters, namely, the polarization intensity (PI), Degree of Linear Polarization (DOLP) and polarization orientation (PO) for comparing these schemes. The first two parameters appear frequently in literature, possibly under different names. The last parameter, polarization orientation, has been introduced and elaborated in this thesis. We have also proposed some extensions/alternatives for the existing imaging and processing schemes and analyzed their advantages. Theoretically and through Monte-Carlo simulations, we have studied the performance of these schemes under white and coloured noise conditions, concluding that, in general, the PMI gives better estimates of all the parameters. Experimental results corroborate our theoretical arguments. PMI is shown to give asymptotically efficient estimates of these parameters, whereas PDI is shown to give biased estimates of the first two and is also shown to be incapable of estimating PO. Moreover, it is shown that PDI is a particular case of PMI. The property of PDI, that it can yield estimates at lower variances has been recognized as its major strength. We have also shown that the three visualization parameters can be fused to form a colour image, giving a holistic view of the scene. We report the advantages of analyzing chunks of data and bootstrapped data under various circumstances. Experiments were conducted to image objects through calibrated scattering media and natural media like mist, with successful results. Scattering media prepared with polystyrene microspheres of diameters 2.97m, 0.06m and 0.13m dispersed in water were used in our experiments. An intensified charge coupled device (CCD) camera was used to capture the images. Results showed that imaging could be performed beyond optical thickness of 40, for particles with 0.13m diameter. For larger particles, the depth to which we could image was much lesser. An experiment using an incoherent source yielded better results than with coherent sources, which we attribute to the speckle noise induced by coherent sources. We have suggested a harmonic based imaging scheme, which can perhaps be used when we have a mixture of scattering particles. We have also briefly touched upon the possible post processing that can be performed on the obtained results, and as an example, shown segmentation based on a PO imaging result.

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Brookshire, Charles Thomas. "Illumination Recovery For Optical Microscopy." University of Dayton / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1588936914060945.

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Koh, P. H. "Methodology of optical topography measurements for functional brain imaging and the development and implementation of functional optical signal analysis software." Thesis, University College London (University of London), 2007. http://discovery.ucl.ac.uk/1444898/.

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Near-infrared spectroscopy (N1RS) has been used extensively in recent years as a non invasive tool for investigating cerebral hemodynamics and oxygenation. The technique exploits the different optical absorption of oxy-haemoglobin and deoxy-haemoglobin in the near infrared region to measure changes in their concentrations in tissue. By making multiple NIRS measurement simultaneously, optical topography (OT) provides spatial maps of the changes in haemoglobin concentration levels from specific regions of the cerebral cortex. The thesis describes several key developments in optical topography studies of functional brain activation. These include the development of a novel data analysis software to process the experimental data and a new statistical methodology for examining the spatial and temporal variance of OT data. The experimental work involved the design of a cognitive task to measure the haemodynamic response using a 24-channeI Hitachi ETG-100 OT system. Following a series of pilot studies, a study on twins with opposite handedness was conducted to study the functional changes in the parietal region of the brain. Changes in systemic variables were also investigated. A dynamic phantom with optical properties similar to those of biological tissues was developed with the use of liquid crystals to simulate spatially varying changes in haemodynamics. A new software tool was developed to provide a flexible processing approach with real time analysis of the optical signals and advanced statistical analysis. Unlike conventional statistical measures which compare a pre-defined activation and task periods, the thesis describes the incorporation of a Statistical Parametric Mapping toolbox which enables statistical inference about the spatially-resolved topographic data to be made. The use of the general linear model computes the temporal correlations between the defined model and optical signals but also corrects for the spatial correlations between neighbouring measurement points. The issues related to collecting functional activation data using optical topography are fully discussed with a view that the work presented in this thesis will extend the applicability of this technology.

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Balu, Ramani. "Intrinsic and Synaptic Properties of Olfactory Bulb Neurons and Their Relation to Olfactory Sensory Processing." Case Western Reserve University School of Graduate Studies / OhioLINK, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=case1173540900.

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Martin, Phillip A., and Phillip A. Martin. "Investigation of the Feasibility of an Optical Imaging System for the Application of In Vivo Flow Cytometry." Thesis, The University of Arizona, 2016. http://hdl.handle.net/10150/621197.

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This thesis investigates the feasibility of employing an optical imaging system for the application of in vivo flow cytometry for detecting rare circulating tumor cells (CTCs) in vasculature. This investigation presented used three optical imaging configurations: a Nikon Eclipse E600 fluorescence microscope with a PIXIS 2048B CCD camera; a Nikon Eclipse E600 fluorescence microscope with a ThorLabs DCC 3240N CMOS camera; and a custom built confocal microendoscope with a ThorLabs DCC 3240N CMOS camera. These systems were employed to gain insight as to what signal to noise ratios and sensitivities are required to sufficiently detect fluorescently labeled cancer cells. This work presents general concepts of fluorescence and confocal microscopy, the experimental setups employed, and experimental measurements and results obtained. The experimental measurements involved the following: the simulation of flow cytometry by imaging green fluorescent microspheres, with a fluorescence excitation range of 505-515 nm and a diameter of 15µm, in a square crit tube moving on a translational stage, and imaging a selection of cells that included MCF10A breast cells (non-cancerous), OVCAR3 ovarian cancer cells, and patient derived xenogram (PDX) breast cancer cells, which express folate-receptor proteins on their surface. We fluorescently labeled these cells with the introduction of a new folate-receptor targeted fluorescent contrast agent OTL38, made by On Target Laboratories. The results established that we were able to image and detect fluorescence microspheres with a minimum signal to noise ratio (SNR) of 2.3 using the ThorLabs DCC 3240N camera on the Nikon Fluorescence microscope. We were able to image and detect the cells used on all three system configurations. Analyzing the different cell uptake efficacies of the contrast agent OTL38, we established that the SNR levels were variable when imaging PDX breast cancer cells. We propose future work to investigate possible effects on the variability of SNR results, as well as, and future steps in designing a real-time optical fluorescence imaging system for in vivo flow cytometry.

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Books on the topic "Intrinsic optical signal imaging"

1

Yoon, Richard S. The characterization of cortical spreading depression in rats using intrinsic optical signal. Ottawa: National Library of Canada, 1996.

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Young, S. Susan. Signal processing and performance analysis for imaging systems. Boston: Artech House, 2008.

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A, Sadjadi Firooz, ed. Selected papers on performance evaluation of signal and image processing systems. Bellingham, Wash., USA: SPIE Optical Engineering Press, 1993.

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V, Guli͡a︡ev I͡U︡, Pape Dennis R, and Fiziko-tekhnicheskiĭ institut im. A.F. Ioffe., eds. International Conference on Optical Information Processing: 2-7 August 1993, St. Petersburg, Russia. Bellingham, Wash., USA: SPIE--the International Society for Optical Engineering, 1993.

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International, Conference on Optical Information Processing (3rd 1999 Moscow Russia). 3rd International Conference on Optical Information Processing: 28-31 May 1999, Moscow, Russia. Bellingham, Wash., USA: SPIE, 1999.

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Remondino, Fabio. TOF Range-Imaging Cameras. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013.

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Yin, Xiaoxia. Terahertz Imaging for Biomedical Applications: Pattern Recognition and Tomographic Reconstruction. Boston, MA: Springer US, 2012.

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A, Velastin Sergio, Remagnino Paolo 1963-, and Institution of Electrical Engineers, eds. Intelligent distributed video surveillance systems. London: Institution of Electrical Engineers, 2006.

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Image processing and pattern recognition: Fundamentals and techniques. Piscataway, NJ: IEEE Press, 2010.

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Wang, Fu Lee. Multimedia and Signal Processing: Second International Conference, CMSP 2012, Shanghai, China, December 7-9, 2012. Proceedings. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.

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Book chapters on the topic "Intrinsic optical signal imaging"

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Tsytsarev, Vassiliy, and Reha S. Erzurumlu. "Voltage-Sensitive Dye and Intrinsic Signal Optical Imaging." In Neurophotonics and Brain Mapping, 101–16. Boca Raton : Taylor & Francis, 2017.: CRC Press, 2017. http://dx.doi.org/10.1201/9781315373058-7.

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Devonshire, Ian M., Ying Zheng, and Jason Berwick. "Voltage Sensitive Dye Imaging, Intrinsic Optical Signals." In Encyclopedia of Computational Neuroscience, 3144–47. New York, NY: Springer New York, 2015. http://dx.doi.org/10.1007/978-1-4614-6675-8_541.

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Devonshire, Ian M., Ying Zheng, and Jason Berwick. "Voltage-Sensitive Dye Imaging, Intrinsic Optical Signals." In Encyclopedia of Computational Neuroscience, 1–4. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4614-7320-6_541-1.

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Tommerdahl, Mark, and Barry Whitsel. "Optical imaging of intrinsic signals in somatosensory cortex." In Somesthesis and the Neurobiology of the Somatosensory Cortex, 369–84. Basel: Birkhäuser Basel, 1996. http://dx.doi.org/10.1007/978-3-0348-9016-8_31.

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Sato, Takayuki, and Manabu Tanifuji. "Optical Intrinsic Signal Imaging for Elucidating Functional Structures in Higher Visual Area." In Neurovascular Coupling Methods, 161–75. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4939-0724-3_8.

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Santos, Edgar, Michael Schöll, Renan Sanchez-Porras, Modar Kentar, Berk Orakcioglu, Andreas Unterberg, Hartmut Dickhaus, and Oliver W. Sakowitz. "Cortical Spreading Depression Dynamics Can Be Studied Using Intrinsic Optical Signal Imaging in Gyrencephalic Animal Cortex." In Brain Edema XV, 93–97. Vienna: Springer Vienna, 2013. http://dx.doi.org/10.1007/978-3-7091-1434-6_16.

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Frostig, Ron D. "Intrinsic Signal Optical Imaging (ISOI): State-of-the-Art with Emphasis on Pre-clinical and Clinical Studies." In Brain Informatics and Health, 111–27. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-6883-1_5.

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Lieke, E. E. "Olfactory Information Processing in Insects Revealed by Real-Time Optical Imaging of Intrinsic Signals." In Advances in Experimental Medicine and Biology, 87–94. Boston, MA: Springer US, 1993. http://dx.doi.org/10.1007/978-1-4899-2468-1_10.

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Yao, Xin-Cheng, and Yi-Chao Li. "Functional Imaging of Retinal Photoreceptors and Inner Neurons Using Stimulus-Evoked Intrinsic Optical Signals." In Retinal Development, 277–85. Totowa, NJ: Humana Press, 2012. http://dx.doi.org/10.1007/978-1-61779-848-1_20.

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Wade, Christopher G. "Intrinsic Rydberg Optical Bistability." In Terahertz Wave Detection and Imaging with a Hot Rydberg Vapour, 39–53. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-94908-6_5.

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Conference papers on the topic "Intrinsic optical signal imaging"

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Yao, Xincheng, and Qiuxiang Zhang. "Intrinsic Optical Signal Imaging of Retinal Function." In Frontiers in Optics. Washington, D.C.: OSA, 2013. http://dx.doi.org/10.1364/fio.2013.ftu4i.4.

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Yao, Xin-Cheng, Lei Liu, and Yang-Guo Li. "Intrinsic optical signal imaging of retinal activity in frog eye." In Seventh International Conference on Photonics and Imaging in Biology and Medicine. SPIE, 2008. http://dx.doi.org/10.1117/12.822000.

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Turley, Jordan A., Michael Nilsson, Frederick Rohan Walker, and Sarah J. Johnson. "A comparison of signal processing techniques for Intrinsic Optical Signal imaging in mice." In 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, 2015. http://dx.doi.org/10.1109/embc.2015.7319828.

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Bauer, Adam Q., Brain R. White, Abraham Z. Snyder, Bradley L. Schlaggar, Jin-Moo Lee, and Joseph P. Culver. "Optical intrinsic signal imaging of functional connectivity in the mouse brain." In Biomedical Optics. Washington, D.C.: OSA, 2012. http://dx.doi.org/10.1364/biomed.2012.bm4a.7.

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Li, Pengcheng, Weihua Luo, Qingming Luo, and Shangbin Cheng. "An evaluation of data analysis methods for optical intrinsic signal imaging." In Third International Conference on Photonics and Imaging in Biology and Medicine, edited by Qingming Luo, Valery V. Tuchin, Min Gu, and Lihong V. Wang. SPIE, 2003. http://dx.doi.org/10.1117/12.546565.

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Jones, David G., and Kathryn M. Murphy. "Magnitude of the intrinsic optical brain imaging signal reflects neural function." In Biomedical Topical Meeting. Washington, D.C.: OSA, 2004. http://dx.doi.org/10.1364/bio.2004.wf13.

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Davoodzadeh, Nami, Mildred s. Cano-Velázquez, David L. Halaney, Carrie R. Jonak, Devin K. Binder, and Guillermo Aguilar. "Evaluation of a transparent cranial implant for multi-wavelength intrinsic optical signal imaging." In Neural Imaging and Sensing 2019, edited by Qingming Luo, Jun Ding, and Ling Fu. SPIE, 2019. http://dx.doi.org/10.1117/12.2511035.

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Zhang, Jiacheng, Yongte Zheng, Shaomin Zhang, and Kedi Xu. "Intrinsic optical imaging revealed precise spatial olfactory information for neural signal recording." In 2017 8th International IEEE/EMBS Conference on Neural Engineering (NER). IEEE, 2017. http://dx.doi.org/10.1109/ner.2017.8008331.

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Yao, Xincheng, Yangguo Li, Yichao Li, and Qiuxiang Zhang. "Intrinsic Optical Signal Imaging of Stimulus-Evoked Neural Activities in the Retina." In Bio-Optics: Design and Application. Washington, D.C.: OSA, 2011. http://dx.doi.org/10.1364/boda.2011.btuc5.

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Luo, Weihua, Pengcheng Li, Li Zhang, Xiaohua Lv, Shaoqun Zeng, and Qingming Luo. "Frame self-division applied in analysis of intrinsic signal optical imaging data." In Biomedical Optics 2006, edited by Valery V. Tuchin. SPIE, 2006. http://dx.doi.org/10.1117/12.645570.

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Reports on the topic "Intrinsic optical signal imaging"

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Speed, Ann Elizabeth, Olga Blum Spahn, and Alan Yuan-Chun Hsu. Final Report on LDRD project 130784 : functional brain imaging by tunable multi-spectral Event-Related Optical Signal (EROS). Office of Scientific and Technical Information (OSTI), September 2009. http://dx.doi.org/10.2172/993885.

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