Relevant bibliographies by topics / 3D medical imaging

Academic literature on the topic '3D medical imaging'

Author: Grafiati
Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "3D medical imaging"

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Squelch, Andrew. "3D printing and medical imaging." Journal of Medical Radiation Sciences 65, no. 3 (September 2018): 171–72. http://dx.doi.org/10.1002/jmrs.300.

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Bhatia, Galub, and Michael Vannier. "3D surface imaging for medical applications." ACM SIGBIO Newsletter 14, no. 3 (September 1994): 7–8. http://dx.doi.org/10.1145/192602.953450.

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Stytz, Martin R., and Rob W. Parrott. "Using kriging for 3d medical imaging." Computerized Medical Imaging and Graphics 17, no. 6 (November 1993): 421–42. http://dx.doi.org/10.1016/0895-6111(93)90059-v.

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Bakalash, Reuven, and Arie Kaufman. "Medicube: A 3D medical imaging architecture." Computers & Graphics 13, no. 2 (January 1989): 151–57. http://dx.doi.org/10.1016/0097-8493(89)90057-5.

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Coatrieux, J. L., C. Toumoulin, C. Hamon, and L. Luo. "Future trends in 3D medical imaging." IEEE Engineering in Medicine and Biology Magazine 9, no. 4 (December 1990): 33–39. http://dx.doi.org/10.1109/51.105216.

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Ney, D. R., and E. K. Fishman. "Editing tools for 3D medical imaging." IEEE Computer Graphics and Applications 11, no. 6 (November 1991): 63–71. http://dx.doi.org/10.1109/38.103395.

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Gunn, Therese. "3. A 3D VIRTUAL MEDICAL IMAGING SUITE." Simulation in Healthcare: The Journal of the Society for Simulation in Healthcare 9, no. 1 (February 2014): 74. http://dx.doi.org/10.1097/01.sih.0000444025.17185.de.

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Gemmeke, H., and N. V. Ruiter. "3D ultrasound computer tomography for medical imaging." Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 580, no. 2 (October 2007): 1057–65. http://dx.doi.org/10.1016/j.nima.2007.06.116.

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Herman, G. T. "A survey of 3D medical imaging technologies." IEEE Engineering in Medicine and Biology Magazine 9, no. 4 (December 1990): 15–17. http://dx.doi.org/10.1109/51.105212.

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Parioti, Evgenia, Stavros Pitoglou, Arianna Filntisi, Athanasios Anastasiou, Ourania Petropoulou, and Dimitris Dionisios Koutsouris. "The Added Value of 3D Imaging and 3D Printing in Head and Neck Surgeries." International Journal of Reliable and Quality E-Healthcare 10, no. 3 (July 2021): 68–81. http://dx.doi.org/10.4018/ijrqeh.2021070105.

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3D imaging and 3D printing are two methods that have been proven very useful in medicine. The objective of 3D medical imaging is to recreate the static and functional anatomy of the inner body. The development of computational systems for image processing and multidimensional monitoring of medical data is important for diagnosis and treatment planning. The technique of 3D printing has enabled the materialization of anatomical models and surgical splints using medical imaging data. The methods of 3D imaging and 3D printing have been utilized in various medical fields such as neuroimaging, neurosurgery, dentistry, otolaryngology and facial plastic surgery. This review aims to evaluate the use of 3D imaging and 3D printing techniques in head and neck surgery and concludes that these technologies have revolutionized medicine. However, improvements in healthcare systems and further research still have to be made to establish their use in everyday medical practices.
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Dissertations / Theses on the topic "3D medical imaging"

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Carr, Jonathan. "Surface reconstruction in 3D medical imaging." Thesis, University of Canterbury. Electrical Engineering, 1996. http://hdl.handle.net/10092/6533.

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This thesis addresses two problems in medical imaging, the development of a system for 3D imaging with ultrasound and a system for making titanium prostheses for cranioplasty. Central to both problems is the construction and depiction of surfaces from volume data where the data is not acquired on a regular grid or is incomplete. A system for acquiring 3D pulse-echo ultrasound data using a conventional 2D ultrasound scanner equipped with an electro-magnetic spatial locator is described. The non-parallel nature of 2D B-scan slices acquired by the system requires the development of new visualisation algorithms to depict three dimensional structures. Two methods for visualising iso-valued surfaces from the ultrasound data are presented. One forms an intermediate volume reconstruction suitable for conventional ray-casting while the second method renders surfaces directly from the slice data. In vivo imaging of human anatomy is used to demonstrate reconstructions of tissue surfaces. Filtering and spatial compounding of scan data is used to reduce speckle. The manifestation of 2D artefacts in 3D surface reconstructions is also illustrated. Pulse-echo ultrasound primarily depicts tissue boundaries. These are characterised by incomplete acoustic interfaces contaminated by noise. The problem of reconstructing tissue interfaces from ultrasound data is viewed as an example of the general problem of reconstructing an object's shape from unorganised surface data. A novel method for reconstructing surfaces in the absence of a priori knowledge of the object's shape, is described and applied to 3D ultrasound data. The method uses projections through the surface data taken from many viewpoints to reconstruct surfaces. Aspects of the method are similar to work in computer vision concerning the determination of the shape of 3D objects from their silhouettes. This work is extended significantly in this thesis by considering the reconstruction of incomplete objects in the presence of noise and through the development of practical algorithms for pixel and voxel data. Furthermore, the reconstruction of realistic, non-convex objects is considered rather than simple geometric objects. 2D and 3D ultrasound data derived from phantoms, as well as artificial data, are used to demonstrate reconstructions. The second problem studied in this thesis concerns designing cranial implants to repair defects in the skull. Skull surfaces are extracted from X-ray CT data by ray-casting iso-valued surfaces. A tensor product B-spline interpolant is used in the ray-caster to reduce ripples in the surface data due to partial voluming and the large spacing between CT slices. The associated surface depth-maps are characterised by large irregular holes which correspond to the defect regions requiring repair. Defects are graphically identified by a user in surface-rendered images. Radial basis function approximation is introduced as a method of interpolating the surface of the skull across these defect regions. The fitted surface is used to produce CNC milling instructions to machine a mould in the shape of the surface from a block of hard plastic resin. A cranial implant is then formed by pressing flat titanium plate into the mould under high pressure in a hydraulic press. The system improves upon current treatment procedures by avoiding the manual aspects of fashioning an implant. It is also suitable when other techniques which use symmetry to reconstruct the skull are inadequate or not possible. The system has been successfully used to treat patients at Christchurch Hospital. Radial basis function (RBF) approximation has previously been restricted to problems where the number of interpolation centres is small. The use of newly developed fast methods for evaluating radial basis interpolants in the surface interpolation software results in a computationally efficient system for designing cranial implants and demonstrates that RBFs are potentially of wide interest in medical imaging and engineering problems where data does not lie on a regular grid.
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Jones, Jonathan-Lee. "2D and 3D segmentation of medical images." Thesis, Swansea University, 2015. https://cronfa.swan.ac.uk/Record/cronfa42504.

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Cardiovascular disease is one of the leading causes of the morbidity and mortality in the western world today. Many different imaging modalities are in place today to diagnose and investigate cardiovascular diseases. Each of these, however, has strengths and weaknesses. There are different forms of noise and artifacts in each image modality that combine to make the field of medical image analysis both important and challenging. The aim of this thesis is develop a reliable method for segmentation of vessel structures in medical imaging, combining the expert knowledge of the user in such a way as to maintain efficiency whilst overcoming the inherent noise and artifacts present in the images. We present results from 2D segmentation techniques using different methodologies, before developing 3D techniques for segmenting vessel shape from a series of images. The main drive of the work involves the investigation of medical images obtained using catheter based techniques, namely Intra Vascular Ultrasound (IVUS) and Optical Coherence Tomography (OCT). We will present a robust segmentation paradigm, combining both edge and region information to segment the media-adventitia, and lumenal borders in those modalities respectively. By using a semi-interactive method that utilizes "soft" constraints, allowing imprecise user input which provides a balance between using the user's expert knowledge and efficiency. In the later part of the work, we develop automatic methods for segmenting the walls of lymph vessels. These methods are employed on sequential images in order to obtain data to reconstruct the vessel walls in the region of the lymph valves. We investigated methods to segment the vessel walls both individually and simultaneously, and compared the results both quantitatively and qualitatively in order obtain the most appropriate for the 3D reconstruction of the vessel wall. Lastly, we adapt the semi-interactive method used on vessels earlier into 3D to help segment out the lymph valve. This involved the user interactive method to provide guidance to help segment the boundary of the lymph vessel, then we apply a minimal surface segmentation methodology to provide segmentation of the valve.
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Quartararo, John David. "Semi-automated segmentation of 3D medical ultrasound images." Worcester, Mass. : Worcester Polytechnic Institute, 2008. http://www.wpi.edu/Pubs/ETD/Available/etd-020509-161314/.

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Thesis (M.S.)--Worcester Polytechnic Institute.
Keywords: 3d ultrasound; ultrasound; image processing; image segmentation; 3d image segmentation; medical imaging Includes bibliographical references (p.142-148).
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Quartararo, John David. "Semi-Automated Segmentation of 3D Medical Ultrasound Images." Digital WPI, 2009. https://digitalcommons.wpi.edu/etd-theses/155.

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A level set-based segmentation procedure has been implemented to identify target object boundaries from 3D medical ultrasound images. Several test images (simulated, scanned phantoms, clinical) were subjected to various preprocessing methods and segmented. Two metrics of segmentation accuracy were used to compare the segmentation results to ground truth models and determine which preprocessing methods resulted in the best segmentations. It was found that by using an anisotropic diffusion filtering method to reduce speckle type noise with a 3D active contour segmentation routine using the level set method resulted in semi-automated segmentation on par with medical doctors hand-outlining the same images.
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Eljaaidi, Abdalla Agila. "2D & 3D ultrasound systems in development of medical imaging technology." Thesis, Cape Peninsula University of Technology, 2016. http://hdl.handle.net/20.500.11838/2193.

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Thesis (MTech (Electrical Engineering))--Cape Peninsula University of Technology, 2016.
Ultrasound is widely used in most medical clinics, especially obstetrical clinics. It is a way of imaging methods that has important diagnostic value. Although useful in many different applications, diagnostic ultrasound is especially useful in antenatal (before delivery) diagnosis. The use of two-dimensional ultrasound (2DUS) in obstetrics has been established. However, there are many disadvantages of 2DUS imaging. Several researchers have published information on the significance of patients being shown the ultrasound screen during examination, especially during three- and four-dimensional (3D/4D) scanning. In addition, a form of ultrasound, called keepsake or entertainment ultrasound, has boomed, particularly in the United States. However, long-term epidemiological studies have failed to show the adverse effects of ultrasound in human tissues. Until now, there is no proof that diagnostic ultrasound causes harm in a human body or the developing foetus when used correctly. While ultrasound is supposed to be absolutely safe, it is a form of energy and, as such, has effects on tissues it traverses (bio-effects). The two most important mechanisms for effects are thermal and non-thermal. These two mechanisms are indicated on the screen of ultrasound devices by two indices: The thermal index (TI) and the mechanical index (MI). These are the purposes of this thesis: • evaluate end-users’ knowledge regarding the safety of ultrasound; • evaluate and make a comparison between acoustic output indices (AOI) in B-mode (2D) and three-dimensional (3D) ultrasound – those measured by thermal (TI) and mechanical (MI) indices; • assess the acoustic output indices (AOI) to benchmark current practice with a survey conducted by the British Medical Ultrasound Society (BMUS); and • review how to design 2D and 3D arrays for medical ultrasound imaging
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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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Badawi, Ramsey Derek. "Aspects of optimisation and qualification in 3D positron emission tomography." Thesis, King's College London (University of London), 1998. https://kclpure.kcl.ac.uk/portal/en/theses/aspects-of-optimisation-and-qualification-in-3d-positron-emission-tomography(47a88023-9d6c-453f-aa8d-fcc5b83ae168).html.

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Pellegrini, Giulio. "Technology development of 3D detectors for high energy physics and medical imaging." Thesis, University of Glasgow, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.269510.

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Rathod, Gaurav Dilip. "An improved effective method for generating 3D printable models from medical imaging." Thesis, Virginia Tech, 2017. http://hdl.handle.net/10919/80415.

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Medical practitioners rely heavily on visualization of medical imaging to get a better understanding of the patient's anatomy. Most cancer treatment and surgery today are performed using medical imaging. Medical imaging is therefore of great importance to the medical industry. Medical imaging continues to depend heavily on a series of 2D scans, resulting in a series of 2D photographs being displayed using light boxes and/or computer monitors. Today, these 2D images are increasingly combined into 3D solid models using software. These 3D models can be used for improved visualization and understanding of the problem at hand, including fabricating physical 3D models using additive manufacturing technologies. Generating precise 3D solid models automatically from 2D scans is non-trivial. Geometric and/or topologic errors are common, and often costly manual editing is required to produce 3D solid models that sufficiently reflect the actual underlying human geometry. These errors arise from the ambiguity of converting from 2D data to 3D data, and also from inherent limitations of the .STL fileformat used in additive manufacturing. This thesis proposes a new, robust method for automatically generating 3D models from 2D scanned data (e.g., computed tomography (CT) or magnetic resonance imaging (MRI)), where the resulting 3D solid models are specifically generated for use with additive manufacturing. This new method does not rely on complicated procedures such as contour evolution and geometric spline generation, but uses volume reconstruction instead. The advantage of this approach is that the original scan data values are kept intact longer, so that the resulting surface is more accurate. This new method is demonstrated using medical CT data of the human nasal airway system, resulting in physical 3D models fabricated via additive manufacturing.
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Li, Jianchun. "Design of an FPGA-based computing platform for realtime 3D medical imaging." online version, 2005. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=case1106098912.

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Books on the topic "3D medical imaging"

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Höhne, Karl Heinz. 3D Imaging in Medicine: Algorithms, Systems, Applications. Berlin, Heidelberg: Springer Berlin Heidelberg, 1990.

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

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Argyriou, Vasileios. Image, video & 3D data registration: Medical, satellite and video processing applications with quality metrics. Hoboken: Wiley, 2015.

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K, Costantini Jay, ed. 3D angiographic atlas of neurovascular anatomy and pathology. Cambridge: Cambridge University Press, 2007.

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Knopp, Tobias. Magnetic Particle Imaging: An Introduction to Imaging Principles and Scanner Instrumentation. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.

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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. Vienna: Springer Vienna, 2009.

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Magnenat-Thalmann, Nadia. Modelling the Physiological Human: 3D Physiological Human Workshop, 3DPH 2009, Zermatt, Switzerland, November 29 – December 2, 2009. Proceedings. Berlin, Heidelberg: Springer-Verlag Berlin Heidelberg, 2009.

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Beolchi, L., and M. H. Kuhn. Medical Imaging: Analysis of Multimodality 2D/3D Images. IOS Press, Incorporated, 1995.

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(Foreword), A. L. Baert, D. Caramella (Editor), and C. Bartolozzi (Editor), eds. 3D Image Processing: Techniques and Clinical Applications (Medical Radiology). Springer, 2002.

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(Foreword), A. L. Baert, A. J. Aschoff (Contributor), C. I. Bartram (Contributor), T. R. Fleiter (Contributor), S. Gottschalk (Contributor), R. Klingebiel (Contributor), N. Meiri (Contributor), et al., eds. Virtual Endoscopy and Related 3D Techniques (Medical Radiology / Diagnostic Imaging). Springer, 2001.

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Book chapters on the topic "3D medical imaging"

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Batchelor, Philip G., P. J. “Eddie” Edwards, and Andrew P. King. "3D Medical Imaging." In 3D Imaging, Analysis and Applications, 445–95. London: Springer London, 2012. http://dx.doi.org/10.1007/978-1-4471-4063-4_11.

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Lavallée, Stéphane, and Philippe Cinquin. "Computer Assisted Medical Interventions." In 3D Imaging in Medicine, 301–12. Berlin, Heidelberg: Springer Berlin Heidelberg, 1990. http://dx.doi.org/10.1007/978-3-642-84211-5_20.

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Ruikar, Darshan D., Dattatray D. Sawat, and K. C. Santosh. "A Systematic Review of 3D Imaging in Biomedical Applications." In Medical Imaging, 154–81. Boca Raton : Taylor & Francis, a CRC title, part of the Taylor & Francis imprint, a member of the Taylor & Francis Group, the academic division of T&F Informa, plc, 2020.: CRC Press, 2019. http://dx.doi.org/10.1201/9780429029417-8.

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Baker, H. Harlyn. "Surface Modeling With Medical Imagery." In 3D Imaging in Medicine, 277–88. Berlin, Heidelberg: Springer Berlin Heidelberg, 1990. http://dx.doi.org/10.1007/978-3-642-84211-5_18.

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Dill, Karin E., Leonid Chepelev, Todd Pietila, and Frank J. Rybicki. "3D Printing from Cardiac CT Images." In Contemporary Medical Imaging, 859–72. Totowa, NJ: Humana Press, 2019. http://dx.doi.org/10.1007/978-1-60327-237-7_66.

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Herman, Gabor T., Sushma S. Trivedi, and Jayaram K. Udupa. "Manipulation of 3D Imagery." In Progress in Medical Imaging, 123–57. New York, NY: Springer New York, 1988. http://dx.doi.org/10.1007/978-1-4612-3866-9_2.

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Fuchs, Henry. "Systems for Display of Three-Dimensional Medical Image Data." In 3D Imaging in Medicine, 315–31. Berlin, Heidelberg: Springer Berlin Heidelberg, 1990. http://dx.doi.org/10.1007/978-3-642-84211-5_21.

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Coatrieux, Jean-Louis, and Christian Barillot. "A Survey of 3D Display Techniques to Render Medical Data." In 3D Imaging in Medicine, 175–95. Berlin, Heidelberg: Springer Berlin Heidelberg, 1990. http://dx.doi.org/10.1007/978-3-642-84211-5_11.

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Pitt, Timothy J., Leonard A. Ferrari, Andy Healey, R. Anthony Reynolds, and Keith N. Humphries. "Splatting and Splines in 3D Medical Ultrasound Imaging." In Acoustical Imaging, 349–55. Boston, MA: Springer US, 1995. http://dx.doi.org/10.1007/978-1-4615-1943-0_36.

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John, Nigel W. "Basis and Principles of Virtual Reality in Medical Imaging." In 3D Image Processing, 279–85. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/978-3-642-59438-0_25.

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Conference papers on the topic "3D medical imaging"

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Schafer, Sebastian, Kenneth R. Hoffmann, Peter B. Noël, and Christina L. Bloebaum. "3D-3D alignment using particle swarm optimization." In Medical Imaging, edited by Joseph M. Reinhardt and Josien P. W. Pluim. SPIE, 2008. http://dx.doi.org/10.1117/12.771685.

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Shamdasani, Vijay, Unmin Bae, Ravi Managuli, and Yongmin Kim. "Improving the visualization of 3D ultrasound data with 3D filtering." In Medical Imaging, edited by Robert L. Galloway, Jr. and Kevin R. Cleary. SPIE, 2005. http://dx.doi.org/10.1117/12.596641.

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West, Jay B., and Calvin R. Maurer, Jr. "A system for finding a 3D target without a 3D image." In Medical Imaging, edited by Michael I. Miga and Kevin R. Cleary. SPIE, 2008. http://dx.doi.org/10.1117/12.771460.

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Vester-Christensen, Martin, Søren G. Erbou, Sune Darkner, and Rasmus Larsen. "Accelerated 3D image registration." In Medical Imaging, edited by Josien P. W. Pluim and Joseph M. Reinhardt. SPIE, 2007. http://dx.doi.org/10.1117/12.709373.

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Zhou, Hua, Wu Qiu, Mingyue Ding, and Songgen Zhang. "Automatic needle segmentation in 3D ultrasound images using 3D improved Hough transform." In Medical Imaging, edited by Michael I. Miga and Kevin R. Cleary. SPIE, 2008. http://dx.doi.org/10.1117/12.770077.

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Lu, Kongkuo, and William E. Higgins. "Improved 3D live-wire method with application to 3D CT chest image analysis." In Medical Imaging, edited by Joseph M. Reinhardt and Josien P. W. Pluim. SPIE, 2006. http://dx.doi.org/10.1117/12.651723.

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Ruijters, Daniel, Drazenko Babic, Robert Homan, Peter Mielekamp, Bart M. ter Haar Romeny, and Paul Suetens. "3D multimodality roadmapping in neuroangiography." In Medical Imaging, edited by Kevin R. Cleary and Michael I. Miga. SPIE, 2007. http://dx.doi.org/10.1117/12.708474.

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Englmeier, Karl-Hans, Markus Siebert, Ruediger von Eisenhart-Rothe, and Heiko Graichen. "Combined registration of 3D tibia and femur implant models in 3D magnetic resonance images." In Medical Imaging, edited by Xiaoping P. Hu and Anne V. Clough. SPIE, 2008. http://dx.doi.org/10.1117/12.769439.

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Littley, Samuel, and Irina Voiculescu. "Interpolation of 3D slice volume data for 3D printing." In SPIE Medical Imaging, edited by Robert J. Webster and Baowei Fei. SPIE, 2017. http://dx.doi.org/10.1117/12.2254616.

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Leung, K. Y. Esther, Marijn van Stralen, Marco M. Voormolen, Gerard van Burken, Attila Nemes, Folkert J. ten Cate, Marcel L. Geleijnse, et al. "Registration of 2D cardiac images to real-time 3D ultrasound volumes for 3D stress echocardiography." In Medical Imaging, edited by Joseph M. Reinhardt and Josien P. W. Pluim. SPIE, 2006. http://dx.doi.org/10.1117/12.652107.

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Reports on the topic "3D medical imaging"

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Martin, Kathi, Nick Jushchyshyn, and Claire King. James Galanos, Silk Chiffon Afternoon Dress c. Fall 1976. Drexel Digital Museum, 2018. http://dx.doi.org/10.17918/q3g5-n257.

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The URL links to a website page in the Drexel Digital Museum (DDM) fashion image archive containing a 3D interactive panorama of an evening suit by American fashion designer James Galanos with related text. This afternoon dress is from Galanos' Fall 1976 collection. It is made from pale pink silk chiffon and finished with hand stitching on the hems and edges of this dress, The dress was gifted to Drexel University as part of The James G. Galanos Archive at Drexel University in 2016. After it was imaged the gown was deemed too fragile to exhibit. By imaging it using high resolution GigaPan technology we are able to create an archival quality digital record of the dress and exhibit it virtually at life size in 3D panorama. The panorama is an HTML5 formatted version of an ultra-high resolution ObjectVR created from stitched tiles captured with GigaPan technology. It is representative the ongoing research of the DDM, an international, interdisciplinary group of researchers focused on production, conservation and dissemination of new media for exhibition of historic fashion.
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