Literatura académica sobre el tema "Computational methods in biomedical optical imaging"
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Artículos de revistas sobre el tema "Computational methods in biomedical optical imaging"
Liu, Xueyan, Dong Peng, Wei Guo, Xibo Ma, Xin Yang y Jie Tian. "Compressed Sensing Photoacoustic Imaging Based on Fast Alternating Direction Algorithm". International Journal of Biomedical Imaging 2012 (2012): 1–7. http://dx.doi.org/10.1155/2012/206214.
Texto completoLaurino, Annunziatina, Alessandra Franceschini, Luca Pesce, Lorenzo Cinci, Alberto Montalbano, Giacomo Mazzamuto, Giuseppe Sancataldo et al. "A Guide to Perform 3D Histology of Biological Tissues with Fluorescence Microscopy". International Journal of Molecular Sciences 24, n.º 7 (4 de abril de 2023): 6747. http://dx.doi.org/10.3390/ijms24076747.
Texto completoZaitsev, Vladimir Y., Sergey Y. Ksenofontov, Alexander A. Sovetsky, Alexander L. Matveyev, Lev A. Matveev, Alexey A. Zykov y Grigory V. Gelikonov. "Real-Time Strain and Elasticity Imaging in Phase-Sensitive Optical Coherence Elastography Using a Computationally Efficient Realization of the Vector Method". Photonics 8, n.º 12 (24 de noviembre de 2021): 527. http://dx.doi.org/10.3390/photonics8120527.
Texto completoSridhar, Chethana, Piyush Kumar Pareek, R. Kalidoss, Sajjad Shaukat Jamal, Prashant Kumar Shukla y Stephen Jeswinde Nuagah. "Optimal Medical Image Size Reduction Model Creation Using Recurrent Neural Network and GenPSOWVQ". Journal of Healthcare Engineering 2022 (26 de febrero de 2022): 1–8. http://dx.doi.org/10.1155/2022/2354866.
Texto completoHauptman, Ami, Ganesh M. Balasubramaniam y Shlomi Arnon. "Machine Learning Diffuse Optical Tomography Using Extreme Gradient Boosting and Genetic Programming". Bioengineering 10, n.º 3 (21 de marzo de 2023): 382. http://dx.doi.org/10.3390/bioengineering10030382.
Texto completoJiang, Yuan, Hao Sha, Shuai Liu, Peiwu Qin y Yongbing Zhang. "AutoUnmix: an autoencoder-based spectral unmixing method for multi-color fluorescence microscopy imaging". Biomedical Optics Express 14, n.º 9 (22 de agosto de 2023): 4814. http://dx.doi.org/10.1364/boe.498421.
Texto completoAkman, Ozgur E., Steven Watterson, Andrew Parton, Nigel Binns, Andrew J. Millar y Peter Ghazal. "Digital clocks: simple Boolean models can quantitatively describe circadian systems". Journal of The Royal Society Interface 9, n.º 74 (12 de abril de 2012): 2365–82. http://dx.doi.org/10.1098/rsif.2012.0080.
Texto completoMostaço-Guidolin, Leila B., Michael S. D. Smith, Mark Hewko, Bernie Schattka, Michael G. Sowa, Arkady Major y Alex C. T. Ko. "Fractal dimension and directional analysis of elastic and collagen fiber arrangement in unsectioned arterial tissues affected by atherosclerosis and aging". Journal of Applied Physiology 126, n.º 3 (1 de marzo de 2019): 638–46. http://dx.doi.org/10.1152/japplphysiol.00497.2018.
Texto completoZhang, Huiting, Dong-Hee Kang, Marie Piantino, Daisuke Tominaga, Takashi Fujimura, Noriyuki Nakatani, J. Nicholas Taylor, Tomomi Furihata, Michiya Matsusaki y Satoshi Fujita. "Rapid Quantification of Microvessels of Three-Dimensional Blood–Brain Barrier Model Using Optical Coherence Tomography and Deep Learning Algorithm". Biosensors 13, n.º 8 (15 de agosto de 2023): 818. http://dx.doi.org/10.3390/bios13080818.
Texto completoChen, Duan, Guo-Wei Wei, Wen-Xiang Cong y Ge Wang. "Computational methods for optical molecular imaging". Communications in Numerical Methods in Engineering 25, n.º 12 (diciembre de 2009): 1137–61. http://dx.doi.org/10.1002/cnm.1164.
Texto completoTesis sobre el tema "Computational methods in biomedical optical imaging"
Birch, Gabriel C. "Computational and Design Methods for Advanced Imaging". Diss., The University of Arizona, 2012. http://hdl.handle.net/10150/242355.
Texto completoBalagopal, Bavishna. "Advanced methods for enhanced sensing in biomedical Raman spectroscopy". Thesis, University of St Andrews, 2014. http://hdl.handle.net/10023/6343.
Texto completoJones, Cameron Christopher. "VALIDATION OF COMPUTATIONAL FLUID DYNAMIC SIMULATIONS OF MEMBRANE ARTIFICIAL LUNGS WITH X-RAY IMAGING". UKnowledge, 2012. http://uknowledge.uky.edu/cbme_etds/2.
Texto completoMontejo, Ludguier. "Computational Methods For The Diagnosis of Rheumatoid Arthritis With Diffuse Optical Tomography". Thesis, 2014. https://doi.org/10.7916/D8NS0S0C.
Texto completoRavi, Prasad K. J. "Development of Efficient Computational Methods for Better Estimation of Optical Properties in Diffuse Optical Tomography". Thesis, 2013. http://etd.iisc.ac.in/handle/2005/3311.
Texto completoRavi, Prasad K. J. "Development of Efficient Computational Methods for Better Estimation of Optical Properties in Diffuse Optical Tomography". Thesis, 2013. http://etd.iisc.ernet.in/2005/3311.
Texto completoGutta, Sreedevi. "Improving photoacoustic imaging with model compensating and deep learning methods". Thesis, 2018. https://etd.iisc.ac.in/handle/2005/4390.
Texto completoNarayana, Swamy Yamuna. "Studies on Kernel Based Edge Detection an Hyper Parameter Selection in Image Restoration and Diffuse Optical Image Reconstruction". Thesis, 2017. http://etd.iisc.ac.in/handle/2005/3615.
Texto completoNarayana, Swamy Yamuna. "Studies on Kernel Based Edge Detection an Hyper Parameter Selection in Image Restoration and Diffuse Optical Image Reconstruction". Thesis, 2017. http://etd.iisc.ernet.in/2005/3615.
Texto completoHarmany, Zachary Taylor. "Computational Optical Imaging Systems: Sensing Strategies, Optimization Methods, and Performance Bounds". Diss., 2012. http://hdl.handle.net/10161/6135.
Texto completoThe emerging theory of compressed sensing has been nothing short of a revolution in signal processing, challenging some of the longest-held ideas in signal processing and leading to the development of exciting new ways to capture and reconstruct signals and images. Although the theoretical promises of compressed sensing are manifold, its implementation in many practical applications has lagged behind the associated theoretical development. Our goal is to elevate compressed sensing from an interesting theoretical discussion to a feasible alternative to conventional imaging, a significant challenge and an exciting topic for research in signal processing. When applied to imaging, compressed sensing can be thought of as a particular case of computational imaging, which unites the design of both the sensing and reconstruction of images under one design paradigm. Computational imaging tightly fuses modeling of scene content, imaging hardware design, and the subsequent reconstruction algorithms used to recover the images.
This thesis makes important contributions to each of these three areas through two primary research directions. The first direction primarily attacks the challenges associated with designing practical imaging systems that implement incoherent measurements. Our proposed snapshot imaging architecture using compressive coded aperture imaging devices can be practically implemented, and comes equipped with theoretical recovery guarantees. It is also straightforward to extend these ideas to a video setting where careful modeling of the scene can allow for joint spatio-temporal compressive sensing. The second direction develops a host of new computational tools for photon-limited inverse problems. These situations arise with increasing frequency in modern imaging applications as we seek to drive down image acquisition times, limit excitation powers, or deliver less radiation to a patient. By an accurate statistical characterization of the measurement process in optical systems, including the inherent Poisson noise associated with photon detection, our class of algorithms is able to deliver high-fidelity images with a fraction of the required scan time, as well as enable novel methods for tissue quantification from intraoperative microendoscopy data. In short, the contributions of this dissertation are diverse, further the state-of-the-art in computational imaging, elevate compressed sensing from an interesting theory to a practical imaging methodology, and allow for effective image recovery in light-starved applications.
Dissertation
Libros sobre el tema "Computational methods in biomedical optical imaging"
V, Tuchin V., ed. Handbook of optical biomedical diagnostics. Bellingham: SPIE Press, 2002.
Buscar texto completoHandbook of optical biomedical diagnostics. Bellingham, Washington: SPIE Press, 2016.
Buscar texto completoTavares, João Manuel R. S. y Paulo Rui Fernandes, eds. New Developments on Computational Methods and Imaging in Biomechanics and Biomedical Engineering. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-23073-9.
Texto completoV, Tuchin V., Izatt Joseph A, Fujimoto James G y Society of Photo-optical Instrumentation Engineers., eds. Coherence domain optical methods in biomedical science and clinical applications V: 23-24 January 2001, San Jose, USA. Bellingham, Wash., USA: SPIE, 2001.
Buscar texto completoLi, Xingde, Qingming Luo y Gu Ying. Optics in health care and biomedical optics IV: 18-20 October 2010, Beijing, China. Editado por SPIE (Society), Zhongguo guang xue xue hui, Beijing gong ye xue yuan, Zhongguo ke xue ji shu xie hui, Guo jia zi ran ke xue ji jin wei yuan hui (China) y China. Guo jia ke xue ji shu bu. Bellingham, Wash: SPIE, 2010.
Buscar texto completoV, Tuchin V., Izatt Joseph A, Fujimoto James G, Society of Photo-optical Instrumentation Engineers. y International Biomedical Optics Society, eds. Coherence domain optical methods in biomedical science and clinical applications IV: 24-26 January 2000, San Jose, California. Bellingham, Wash., USA: SPIE, 2000.
Buscar texto completoV, Tuchin V., Izatt Joseph A, Fujimoto James G y Society of Photo-optical Instrumentation Engineers., eds. Coherence domain optical methods in biomedical science and clinical applications VI: 21-23 January 2002, San Jose, USA. Bellingham, Wash: SPIE, 2002.
Buscar texto completoV, Tuchin V., Izatt Joseph A, Society of Photo-optical Instrumentation Engineers. y International Biomedical Optics Society, eds. Proceedings of coherence domain optical methods in biomedical science and clinical applications II: 27-28 January 1998, San Jose, California. Bellingham, Wash., USA: SPIE, 1998.
Buscar texto completoAntoni, Nowakowski, Kosmowski Bogdan B, Society of Photo-optical Instrumentation Engineers., Politechnika Gdańska. Katedra Inżynierii Biomedycznej. y Poland. Ministerstwo Nauki i Informatyzacji., eds. Optical methods, sensors, image processing, and visualization in medicine: 10-13 September, 2003, Gdansk, Poland. Bellingham, Wash: SPIE, 2004.
Buscar texto completoHandbook of biomedical optics. Boca Raton: CRC Press, 2011.
Buscar texto completoCapítulos de libros sobre el tema "Computational methods in biomedical optical imaging"
Garini, Yuval y Elad Tauber. "Spectral Imaging: Methods, Design, and Applications". En Biomedical Optical Imaging Technologies, 111–61. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-28391-8_4.
Texto completoTavares, João Manuel R. S. y Paulo Rui Fernandes. "Correction to: New Developments on Computational Methods and Imaging in Biomechanics and Biomedical Engineering". En Lecture Notes in Computational Vision and Biomechanics, C1. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-23073-9_11.
Texto completoLiu, Jianfei, Q. Jackie Wu, Fang-Fang Yin, John P. Kirkpatrick, Alvin Cabrera y Yaorong Ge. "An Active Optical Flow Model for Dose Prediction in Spinal SBRT Plans". En Recent Advances in Computational Methods and Clinical Applications for Spine Imaging, 27–35. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-14148-0_3.
Texto completoSevick-Muraca, Eva M. "[31] Computations of time-dependent photon migration for biomedical optical imaging". En Part B: Numerical Computer Methods, 748–81. Elsevier, 1994. http://dx.doi.org/10.1016/s0076-6879(94)40070-9.
Texto completo"Medical Imaging Instrumentation and Techniques". En Computational Optical Biomedical Spectroscopy and Imaging, 381–408. CRC Press, 2015. http://dx.doi.org/10.1201/b18024-17.
Texto completo"Developing a Comprehensive Taxonomy for Human Cell Types". En Computational Optical Biomedical Spectroscopy and Imaging, 143–72. CRC Press, 2015. http://dx.doi.org/10.1201/b18024-10.
Texto completo"Functional Near-Infrared Spectroscopy and Its Applications in Neurosciences". En Computational Optical Biomedical Spectroscopy and Imaging, 173–94. CRC Press, 2015. http://dx.doi.org/10.1201/b18024-11.
Texto completo"Computer-Aided Diagnosis of Interstitial Lung Diseases Based on Computed Tomography Image Analysis". En Computational Optical Biomedical Spectroscopy and Imaging, 195–220. CRC Press, 2015. http://dx.doi.org/10.1201/b18024-12.
Texto completo"Induced Optical Natural Fluorescence Spectroscopy for Giardia lamblia Cysts". En Computational Optical Biomedical Spectroscopy and Imaging, 221–58. CRC Press, 2015. http://dx.doi.org/10.1201/b18024-13.
Texto completo"Strong Interaction between Nanophotonic Structures for Their Applications on Optical Biomedical Spectroscopy and Imaging". En Computational Optical Biomedical Spectroscopy and Imaging, 259–80. CRC Press, 2015. http://dx.doi.org/10.1201/b18024-14.
Texto completoActas de conferencias sobre el tema "Computational methods in biomedical optical imaging"
Ripoll, Jorge, Vasilis Ntziachristos y Eleftherios N. Economou. "Experimental demonstration of a fast analytical method for modeling photon propagation in diffusive media with arbitrary geometry". En European Conference on Biomedical Optics. Washington, D.C.: Optica Publishing Group, 2001. http://dx.doi.org/10.1364/ecbo.2001.4431_233.
Texto completoKim, Chang-Keun, Keong-Jin Lee, Dong-Choon Hwang, Seung-Cheol Kim y Eun-Soo Kim. "IVR-based computational reconstruction method in three-dimensional integral imaging with non-uniform lens array". En Biomedical Optics. Washington, D.C.: OSA, 2008. http://dx.doi.org/10.1364/biomed.2008.jma1.
Texto completoShin, Dong-Hak y Hoon Yoo. "3D image quality enhancement in computational integral imaging system by additional use of an interpolation method". En Biomedical Optics. Washington, D.C.: OSA, 2008. http://dx.doi.org/10.1364/biomed.2008.jma5.
Texto completoEspañol, Malena I., Suren Jayasuriya y Mohit Malu. "Multilevel Methods for Imaging Applications". En Computational Optical Sensing and Imaging. Washington, D.C.: OSA, 2020. http://dx.doi.org/10.1364/cosi.2020.cth4c.1.
Texto completoSchultz, Christian. "The Potential of Optical Methods in Molecular Imaging". En Biomedical Topical Meeting. Washington, D.C.: OSA, 2006. http://dx.doi.org/10.1364/bio.2006.tub3.
Texto completoPaes, Stephane, Seon Young Ryu, Jihoon Na, Eun Seo Choi y Byeong Ha Lee. "Application of iterative deconvolution methods for optical coherent imaging". En Biomedical Optics 2005, editado por Valery V. Tuchin, Joseph A. Izatt y James G. Fujimoto. SPIE, 2005. http://dx.doi.org/10.1117/12.592876.
Texto completoOliveri, Giacomo y Toshifumi Moriyama. "Compressive Sensing Methods Applied to Inverse Imaging Problems". En Computational Optical Sensing and Imaging. Washington, D.C.: OSA, 2014. http://dx.doi.org/10.1364/cosi.2014.cw2c.3.
Texto completoKaur, S., J. Gomez-Blanco, A. Khalifa, S. Adinarayanan, R. Sanchez-Garcia, D. Wrapp, J. S. McLellan, K. H. Bui y J. Vargas. "Local methods to improve cryo-electron microcopy maps". En Computational Optical Sensing and Imaging. Washington, D.C.: OSA, 2021. http://dx.doi.org/10.1364/cosi.2021.ctu4b.3.
Texto completoJohnson, Gregory E., Ash K. Macon y Goran M. Rauker. "Computational imaging design tools and methods". En Optical Science and Technology, the SPIE 49th Annual Meeting, editado por Jose M. Sasian, R. John Koshel, Paul K. Manhart y Richard C. Juergens. SPIE, 2004. http://dx.doi.org/10.1117/12.558068.
Texto completoLepage, K. y S. Kraut. "Multitaper Methods for Spectrum Estimation with a Rotational Shear Interferometer". En Computational Optical Sensing and Imaging. Washington, D.C.: OSA, 2005. http://dx.doi.org/10.1364/cosi.2005.ctuc3.
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