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1

Imber, Brandon S., Andrew L. Lin, Zhigang Zhang, Krishna Nand Keshavamurthy, Amy Robin Deipolyi, Kathryn Beal, Marc A. Cohen, et al. "Comparison of Radiographic Approaches to Assess Treatment Response in Pituitary Adenomas: Is RECIST or RANO Good Enough?" Journal of the Endocrine Society 3, no. 9 (July 2, 2019): 1693–706. http://dx.doi.org/10.1210/js.2019-00130.

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Abstract Context Pituitary adenomas (PA) are often irregularly shaped, particularly posttreatment. There are no standardized radiographic criteria for assessing treatment response, substantially complicating interpretation of prospective outcome data. Existing imaging frameworks for intracranial tumors assume perfectly spherical targets and may be suboptimal. Objective To compare a three-dimensional (3D) volumetric approach against accepted surrogate measurements to assess PA posttreatment response (PTR). Design Retrospective review of patients with available pre- and postradiotherapy (RT) imaging. A neuroradiologist determined tumor sizes in one dimensional (1D) per Response Evaluation in Solid Tumors (RECIST) criteria, two dimensional (2D) per Response Assessment in Neuro-Oncology (RANO) criteria, and 3D estimates assuming a perfect sphere or perfect ellipsoid. Each tumor was manually segmented for 3D volumetric measurements. The Hakon Wadell method was used to calculate sphericity. Setting Tertiary cancer center. Patients or Other Participants Patients (n = 34, median age = 50 years; 50% male) with PA and MRI scans before and after sellar RT. Interventions Patients received sellar RT for intact or surgically resected lesions. Main Outcome Measure(s) Radiographic PTR, defined as percent tumor size change. Results Using 3D volumetrics, mean sphericity = 0.63 pre-RT and 0.60 post-RT. With all approaches, most patients had stable disease on post-RT scan. PTR for 1D, 2D, and 3D spherical measurements were moderately well correlated with 3D volumetrics (e.g., for 1D: 0.66, P < 0.0001) and were superior to 3D ellipsoid. Intraclass correlation coefficient demonstrated moderate to good reliability for 1D, 2D, and 3D sphere (P < 0.001); 3D ellipsoid was inferior (P = 0.009). 3D volumetrics identified more potential partially responding and progressive lesions. Conclusions Although PAs are irregularly shaped, 1D and 2D approaches are adequately correlated with volumetric assessment.
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Arghavani, J., and G. Abdou. "3D volumetric pallet-loading optimisation." International Journal of Advanced Manufacturing Technology 11, no. 6 (November 1996): 425–29. http://dx.doi.org/10.1007/bf01178968.

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Park, Ji Hun. "3D Mosaic from Images." Applied Mechanics and Materials 752-753 (April 2015): 1081–84. http://dx.doi.org/10.4028/www.scientific.net/amm.752-753.1081.

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This paper presents a tool for 3D object mosaic. Given a set of background removed input images, we first compute a 3D reconstructed volumetric model body using shape from silhouette. The granularity of a volumetric body is the user input. Voxel center coordinates, voxel color, and surface normal of the voxel are computed for 3D mosaic. The voxels of reconstructed volumetric body are replaced by primitive shapes such as sphere, cylinder, cone, etc. We call this process as a 3D mosaic. The background-eliminated input images may contain information on body parts supplied by a user. Using information on body parts, only a part of 3D reconstructed volumetric body is replaced by a new shape while the rest of body retains voxel information. The surface normal values are used for primitive shapes with direction such as a cone. 3D mosaic can be used for emphasizing or deemphasizing a part of 3D reconstructed model body, similar to the function of a 2D image mosaic. Emphasizing and deemphasizing is done by resolution, surface normal, size of body parts, color and/or shape of the 3D primitive object.
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YANG Guang-lei, 杨光磊, 井长龙 JING Chang-long, 裴治棋 PEI Zhi-qi, 张应松 ZHANG Ying-song, 宋志刚 SONG Zhi-gang, and 冯奇斌 FENG Qi-bin. "Solid-state volumetric true 3D display." Chinese Journal of Liquid Crystals and Displays 30, no. 1 (2015): 137–42. http://dx.doi.org/10.3788/yjyxs20153001.0137.

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Patel, Toral S. "3D Volumetric Visualization of MRI Images¬¬." International Journal for Research in Applied Science and Engineering Technology 6, no. 4 (April 30, 2018): 973–76. http://dx.doi.org/10.22214/ijraset.2018.4165.

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Janaszewski, Marcin, Michel Couprie, and Laurent Babout. "Hole filling in 3D volumetric objects." Pattern Recognition 43, no. 10 (October 2010): 3548–59. http://dx.doi.org/10.1016/j.patcog.2010.04.015.

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7

Regehly, Martin, Yves Garmshausen, Marcus Reuter, Niklas F. König, Eric Israel, Damien P. Kelly, Chun-Yu Chou, Klaas Koch, Baraa Asfari, and Stefan Hecht. "Xolography for linear volumetric 3D printing." Nature 588, no. 7839 (December 23, 2020): 620–24. http://dx.doi.org/10.1038/s41586-020-3029-7.

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Favalora, G. E. "Volumetric 3D displays and application infrastructure." Computer 38, no. 8 (August 2005): 37–44. http://dx.doi.org/10.1109/mc.2005.276.

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Osipov, L. V., N. S. Kulberg, D. V. Leonov, and S. P. Morozov. "3D Ultrasound: Visualization of Volumetric Data." Biomedical Engineering 54, no. 2 (July 2020): 149–54. http://dx.doi.org/10.1007/s10527-020-09993-3.

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Chromy, Adam. "Application of High-Resolution 3D Scanning in Medical Volumetry." International Journal of Electronics and Telecommunications 62, no. 1 (March 1, 2016): 23–31. http://dx.doi.org/10.1515/eletel-2016-0003.

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Abstract This paper deals with application of 3D scanning technology in medicine. Important properties of 3D scanners are discussed with emphasize on medical applications. Construction of medical 3D scanner according to these specifications is described and practical application of its use in medical volumetry is presented. Besides volumetry, such 3D scanner is usable for many other purposes, like monitoring of recovery process, ergonomic splint manufacturing or inflammation detection. 3D scanning introduces novel volumetric method, which is compared with standard methods. The new method is more accurate compared to present ones. Principles of this method are discussed in paper and its accuracy is evaluated and experimentally verified.
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Panke, Karola, Tatjana Pladere, Mara Velina, Aiga Svede, and Gunta Krumina. "Objective User Visual Experience Evaluation When Working with Virtual Pixel-Based 3D System and Real Voxel-Based 3D System." Photonics 6, no. 4 (October 16, 2019): 106. http://dx.doi.org/10.3390/photonics6040106.

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Volumetric display shows promising implications for healthcare related applications as an innovative technology that creates real three-dimensional (3D) image by illuminating points in three-dimensional space to generate volumetric images without image separation. We used eccentric photorefractometry to objectively study ocular performance in a practical environment by evaluating near work-induced refraction shift, accommodative microfluctuations, and pupil size for 38 young adults after viewing anaglyph, and volumetric 3D content for prolonged time. The results of our study demonstrate that participants who performed relative depth estimation task on volumetric 3D content were less likely to experience task-induced myopic refraction shift. For both 3D content types, we observed pupil constriction, that is possibly related to visual fatigue. For anaglyph 3D pupil constriction, onset was observed significantly sooner, compared to volumetric 3D. Overall, sustained work with 3D content, and small disparities or the fully eliminated possibility of accommodation-vergence conflict, not only minimizes near work-induced myopic shift, but also provide beneficial accommodation relaxation that was demonstrated in this study as hypermetropic shift for nearly half of participants.
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Ying, Shen, Renzhong Guo, Lin Li, Peter Van Oosterom, and Jantien Stoter. "Construction of 3D Volumetric Objects for a 3D Cadastral System." Transactions in GIS 19, no. 5 (November 25, 2014): 758–79. http://dx.doi.org/10.1111/tgis.12129.

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Huang, Wenlong, Brian Lai, Weijian Xu, and Zhuowen Tu. "3D Volumetric Modeling with Introspective Neural Networks." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 8481–88. http://dx.doi.org/10.1609/aaai.v33i01.33018481.

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In this paper, we study the 3D volumetric modeling problem by adopting the Wasserstein introspective neural networks method (WINN) that was previously applied to 2D static images. We name our algorithm 3DWINN which enjoys the same properties as WINN in the 2D case: being simultaneously generative and discriminative. Compared to the existing 3D volumetric modeling approaches, 3DWINN demonstrates competitive results on several benchmarks in both the generation and the classification tasks. In addition to the standard inception score, the Frechet Inception Distance (FID) metric is´ also adopted to measure the quality of 3D volumetric generations. In addition, we study adversarial attacks for volumetric data and demonstrate the robustness of 3DWINN against adversarial examples while achieving appealing results in both classification and generation within a single model. 3DWINN is a general framework and it can be applied to the emerging tasks for 3D object and scene modeling.1
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Xing, Weiwei, Weibin Liu, and Baozong Yuan. "3D Object Classification Based on Volumetric Parts." International Journal of Cognitive Informatics and Natural Intelligence 2, no. 1 (January 2008): 87–99. http://dx.doi.org/10.4018/jcini.2008010107.

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Geng, Jason. "Volumetric 3D Display for Radiation Therapy Planning." Journal of Display Technology 4, no. 4 (December 2008): 437–50. http://dx.doi.org/10.1109/jdt.2008.922413.

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Cajal, C., J. Santolaria, J. Velazquez, S. Aguado, and J. Albajez. "Volumetric Error Compensation Technique for 3D Printers." Procedia Engineering 63 (2013): 642–49. http://dx.doi.org/10.1016/j.proeng.2013.08.276.

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McIntyre, N. S., D. M. Kingston, P. A. W. van der Heide, M. L. Wagter, M. B. Stanley, and A. H. Clarke. "Volumetric rendering of 3D SIMS depth profiles." Proceedings, annual meeting, Electron Microscopy Society of America 54 (August 11, 1996): 1050–51. http://dx.doi.org/10.1017/s0424820100167718.

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Dynamic secondary ion mass spectrometry (SIMS) can be used to uncover unique information about interfaces and whole structures which are “buried” within a solid. During a depth profile of a solid, a sequence of SIMS images is acquired for each element under study The sequence is correlated into a vertical “stack” which contains digitised three dimensional (3D) elemental distributions. Although such distributions are distorted by surface roughness, preferential sputtering and SIMS matrix effects, there is still considerable structural information contained in the volume and much potential for further information retrieval as the above-mentioned distorting effects are addressedOne of the major tools used to assess distributional information within the 3D volume has been visual rendering software. Using Sunvision software (Sun Microsystems Inc.) and a small workstation, images of the volume can be constructed which display pixels either in a “maximum value” perspective or in perspectives where the density of each phase can be adjusted to maximise structural detail.Several examples of the technique will be shown.
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Jing, Chang Long, Qi Bin Feng, Ying Song Zhang, Guang Lei Yang, Zhi Gang Song, Zhi Qi Pei, and Guo Qiang Lv. "LED-Based 3-DMD Volumetric 3D Display." Applied Mechanics and Materials 596 (July 2014): 442–45. http://dx.doi.org/10.4028/www.scientific.net/amm.596.442.

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A solid-state volumetric true 3D display developed by Hefei University of Technology consists of two main components: a high-speed video projector and a stack of liquid crystal shutters. The shutters are based on polymer stabilized cholesteric texture material, presenting different states that can be switched by different voltage. The high-speed video projector includes LED-based light source and tree-chip digital micro-mirror devices modulating RGB lights. A sequence of slices of three-dimensional images are projected into the liquid crystal shutters locating at the proper depth, forming a true 3D image depending on the human vision persistence. The prototype is developed. The measurement results show that the screen brightness can reach 149 nit and no flickers can be perceived.
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Saito, Shunsuke, Liwen Hu, Chongyang Ma, Hikaru Ibayashi, Linjie Luo, and Hao Li. "3D hair synthesis using volumetric variational autoencoders." ACM Transactions on Graphics 37, no. 6 (January 10, 2019): 1–12. http://dx.doi.org/10.1145/3272127.3275019.

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Walz, Patrick, Zachary Robinett, Claudia Kirsch, Matthew L. Bush, and D. Bradley Welling. "3D Volumetric Conformal Analysis of Vestibular Schwannomas." Otolaryngology–Head and Neck Surgery 145, no. 2_suppl (August 2011): P202. http://dx.doi.org/10.1177/0194599811415823a221.

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Kaufman, Arie, Roni Yagel, and Reuven Bakalash. "Direct interaction with a 3D volumetric environment." ACM SIGGRAPH Computer Graphics 24, no. 2 (March 1990): 33–34. http://dx.doi.org/10.1145/91394.91407.

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Li, Jituo, and Guodong Lu. "Customizing 3D garments based on volumetric deformation." Computers in Industry 62, no. 7 (September 2011): 693–707. http://dx.doi.org/10.1016/j.compind.2011.04.002.

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Tubic, Dragan, Patrick Hébert, and Denis Laurendeau. "A volumetric approach for interactive 3D modeling." Computer Vision and Image Understanding 92, no. 1 (October 2003): 56–77. http://dx.doi.org/10.1016/j.cviu.2003.07.001.

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Shou, Yufeng. "Thiol-ene materials promote volumetric 3D printing." MRS Bulletin 46, no. 1 (January 2021): 12. http://dx.doi.org/10.1557/s43577-020-00003-1.

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Maruyama, Yutaka, Norio Yoshida, Hiroto Tadano, Daisuke Takahashi, Mitsuhisa Sato, and Fumio Hirata. "Massively parallel implementation of 3D-RISM calculation with volumetric 3D-FFT." Journal of Computational Chemistry 35, no. 18 (April 28, 2014): 1347–55. http://dx.doi.org/10.1002/jcc.23619.

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26

Nobles, Gary R., and Christopher H. Roosevelt. "Filling the Void in Archaeological Excavations: 2D Point Clouds to 3D Volumes." Open Archaeology 7, no. 1 (January 1, 2021): 589–614. http://dx.doi.org/10.1515/opar-2020-0149.

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Abstract 3D data captured from archaeological excavations are frequently left to speak for themselves. 3D models of objects are uploaded to online viewing platforms, the tops or bottoms of surfaces are visualised in 2.5D, or both are reduced to 2D representations. Representations of excavation units, in particular, often remain incompletely processed as raw surface outputs, unable to be considered individual entities that represent the individual, volumetric units of excavation. Visualisations of such surfaces, whether as point clouds or meshes, are commonly viewed as an end result in and of themselves, when they could be considered the beginning of a fully volumetric way of recording and understanding the 3D archaeological record. In describing the creation of an archaeologically focused recording routine and a 3D-focused data processing workflow, this article provides the means to fill the void between excavation-unit surfaces, thereby producing an individual volumetric entity that corresponds to each excavation unit. Drawing on datasets from the Kaymakçı Archaeological Project (KAP) in western Turkey, the article shows the potential for programmatic creation of volumetric contextual units from 2D point cloud datasets, opening a world of possibilities and challenges for the development of a truly 3D archaeological practice.
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Tantaoui, Meriem, Mustapha Krim, Ismail Ghazi, Zineb Sobhy, Abdelkrim Kartouni, Hamid Chakir, Abdenebi El Moutawakkil, and Souha Sahraoui. "Dosimetric Comparison of 3D Conformal Radiotherapy (3D-CRT) and Volumetric Modulated Arc Therapy (VMAT®) in Prostate Cancer." Journal of Advanced Research in Dynamical and Control Systems 11, no. 11-SPECIAL ISSUE (February 20, 2019): 653–59. http://dx.doi.org/10.5373/jardcs/v11sp11/20193080.

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Akca, Devrim, Efstratios Stylianidis, Konstantinos Smagas, Martin Hofer, Daniela Poli, Armin Gruen, Victor Sanchez Martin, et al. "VOLUMETRIC FOREST CHANGE DETECTION THROUGH VHR SATELLITE IMAGERY." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B8 (June 24, 2016): 1213–20. http://dx.doi.org/10.5194/isprsarchives-xli-b8-1213-2016.

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Quick and economical ways of detecting of planimetric and volumetric changes of forest areas are in high demand. A research platform, called FORSAT (A satellite processing platform for high resolution forest assessment), was developed for the extraction of 3D geometric information from VHR (very-high resolution) imagery from satellite optical sensors and automatic change detection. This 3D forest information solution was developed during a Eurostars project. FORSAT includes two main units. The first one is dedicated to the geometric and radiometric processing of satellite optical imagery and 2D/3D information extraction. This includes: image radiometric pre-processing, image and ground point measurement, improvement of geometric sensor orientation, quasiepipolar image generation for stereo measurements, digital surface model (DSM) extraction by using a precise and robust image matching approach specially designed for VHR satellite imagery, generation of orthoimages, and 3D measurements in single images using mono-plotting and in stereo images as well as triplets. FORSAT supports most of the VHR optically imagery commonly used for civil applications: IKONOS, OrbView – 3, SPOT – 5 HRS, SPOT – 5 HRG, QuickBird, GeoEye-1, WorldView-1/2, Pléiades 1A/1B, SPOT 6/7, and sensors of similar type to be expected in the future. The second unit of FORSAT is dedicated to 3D surface comparison for change detection. It allows users to import digital elevation models (DEMs), align them using an advanced 3D surface matching approach and calculate the 3D differences and volume changes between epochs. To this end our 3D surface matching method LS3D is being used. FORSAT is a single source and flexible forest information solution with a very competitive price/quality ratio, allowing expert and non-expert remote sensing users to monitor forests in three and four dimensions from VHR optical imagery for many forest information needs. The capacity and benefits of FORSAT have been tested in six case studies located in Austria, Cyprus, Spain, Switzerland and Turkey, using optical data from different sensors and with the purpose to monitor forest with different geometric characteristics. The validation run on Cyprus dataset is reported and commented.
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Akca, Devrim, Efstratios Stylianidis, Konstantinos Smagas, Martin Hofer, Daniela Poli, Armin Gruen, Victor Sanchez Martin, et al. "VOLUMETRIC FOREST CHANGE DETECTION THROUGH VHR SATELLITE IMAGERY." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B8 (June 24, 2016): 1213–20. http://dx.doi.org/10.5194/isprs-archives-xli-b8-1213-2016.

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Quick and economical ways of detecting of planimetric and volumetric changes of forest areas are in high demand. A research platform, called FORSAT (A satellite processing platform for high resolution forest assessment), was developed for the extraction of 3D geometric information from VHR (very-high resolution) imagery from satellite optical sensors and automatic change detection. This 3D forest information solution was developed during a Eurostars project. FORSAT includes two main units. The first one is dedicated to the geometric and radiometric processing of satellite optical imagery and 2D/3D information extraction. This includes: image radiometric pre-processing, image and ground point measurement, improvement of geometric sensor orientation, quasiepipolar image generation for stereo measurements, digital surface model (DSM) extraction by using a precise and robust image matching approach specially designed for VHR satellite imagery, generation of orthoimages, and 3D measurements in single images using mono-plotting and in stereo images as well as triplets. FORSAT supports most of the VHR optically imagery commonly used for civil applications: IKONOS, OrbView – 3, SPOT – 5 HRS, SPOT – 5 HRG, QuickBird, GeoEye-1, WorldView-1/2, Pléiades 1A/1B, SPOT 6/7, and sensors of similar type to be expected in the future. The second unit of FORSAT is dedicated to 3D surface comparison for change detection. It allows users to import digital elevation models (DEMs), align them using an advanced 3D surface matching approach and calculate the 3D differences and volume changes between epochs. To this end our 3D surface matching method LS3D is being used. FORSAT is a single source and flexible forest information solution with a very competitive price/quality ratio, allowing expert and non-expert remote sensing users to monitor forests in three and four dimensions from VHR optical imagery for many forest information needs. The capacity and benefits of FORSAT have been tested in six case studies located in Austria, Cyprus, Spain, Switzerland and Turkey, using optical data from different sensors and with the purpose to monitor forest with different geometric characteristics. The validation run on Cyprus dataset is reported and commented.
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Qu, Lei, Changfeng Wu, and Liang Zou. "3D Dense Separated Convolution Module for Volumetric Medical Image Analysis." Applied Sciences 10, no. 2 (January 9, 2020): 485. http://dx.doi.org/10.3390/app10020485.

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With the thriving of deep learning, 3D convolutional neural networks have become a popular choice in volumetric image analysis due to their impressive 3D context mining ability. However, the 3D convolutional kernels will introduce a significant increase in the amount of trainable parameters. Considering the training data are often limited in biomedical tasks, a trade-off has to be made between model size and its representational power. To address this concern, in this paper, we propose a novel 3D Dense Separated Convolution (3D-DSC) module to replace the original 3D convolutional kernels. The 3D-DSC module is constructed by a series of densely connected 1D filters. The decomposition of 3D kernel into 1D filters reduces the risk of overfitting by removing the redundancy of 3D kernels in a topologically constrained manner, while providing the infrastructure for deepening the network. By further introducing nonlinear layers and dense connections between 1D filters, the network’s representational power can be significantly improved while maintaining a compact architecture. We demonstrate the superiority of 3D-DSC on volumetric medical image classification and segmentation, which are two challenging tasks often encountered in biomedical image computing.
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FENG Qi-bin, 冯奇斌, 王小丽 WANG Xiao-li, 吕国强 LV Guo-qiang, and 吴华夏 WU Hua-xia. "Colorimetric Characters of Solid Volumetric True 3D Display." Chinese Journal of Liquid Crystals and Displays 26, no. 1 (2011): 100–104. http://dx.doi.org/10.3788/yjyxs20112601.0100.

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LU Yun-long, 芦云龙, 盛杰超 SHENG Jie-chao, 方. 勇. FANG Yong, and 吕国强 LV Guo-qiang. "Optimizing effect of solid volumetric true 3D display." Chinese Journal of Liquid Crystals and Displays 31, no. 5 (2016): 518–23. http://dx.doi.org/10.3788/yjyxs20163105.0518.

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de Oliveira, Luı́s F., Ricardo T. Lopes, Edgar F. O. de Jesus, and Delson Braz. "3D X-ray tomography to evaluate volumetric objects." Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 505, no. 1-2 (June 2003): 573–76. http://dx.doi.org/10.1016/s0168-9002(03)01150-1.

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Lutz, Anja, Jan Paul, Axel Bornstedt, Gerd Nienhaus, Patrick Etyngier, Peter Bernhardt, Wolfgang Rottbauer, and Volker Rasche. "Volumetric motion quantification by 3D velocity encoded MRI." Journal of Cardiovascular Magnetic Resonance 14, Suppl 1 (2012): P247. http://dx.doi.org/10.1186/1532-429x-14-s1-p247.

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Guerchouche, R., O. Bernier, and T. Zaharia. "Multiresolution volumetric 3D object reconstruction for collaborative interactions." Pattern Recognition and Image Analysis 18, no. 4 (December 2008): 621–37. http://dx.doi.org/10.1134/s1054661808040147.

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Delanoy, Johanna, Mathieu Aubry, Phillip Isola, Alexei A. Efros, and Adrien Bousseau. "3D Sketching using Multi-View Deep Volumetric Prediction." Proceedings of the ACM on Computer Graphics and Interactive Techniques 1, no. 1 (July 25, 2018): 1–22. http://dx.doi.org/10.1145/3203197.

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Grossman, Tovi, Daniel Wigdor, and Ravin Balakrishnan. "Multi-finger gestural interaction with 3D volumetric displays." ACM Transactions on Graphics 24, no. 3 (July 2005): 931. http://dx.doi.org/10.1145/1073204.1073287.

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Khan, Javid, Christopher Blackwell, Chi Can, and Ian Underwood. "16-1: Invited Paper: Holographic Volumetric 3D Displays." SID Symposium Digest of Technical Papers 49, no. 1 (May 2018): 177–80. http://dx.doi.org/10.1002/sdtp.12513.

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Huamán, M. H. G. "P28.04: Volumetric ultrasonography (3D/4D) in early pregnancy." Ultrasound in Obstetrics and Gynecology 30, no. 4 (September 21, 2007): 558. http://dx.doi.org/10.1002/uog.4732.

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Laves, Max-Heinrich, Lüder A. Kahrs, and Tobias Ortmaier. "Volumetric 3D stitching of optical coherence tomography volumes." Current Directions in Biomedical Engineering 4, no. 1 (September 1, 2018): 327–30. http://dx.doi.org/10.1515/cdbme-2018-0079.

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AbstractOptical coherence tomography (OCT) is a noninvasive medical imaging modality, which provides highresolution transectional images of biological tissue. However, its potential is limited due to a relatively small field of view. To overcome this drawback, we describe a scheme for fully automated stitching of multiple 3D OCT volumes for panoramic imaging. The voxel displacements between two adjacent images are calculated by extending the Lucas-Kanade optical flow a lgorithm to dense volumetric images. A RANSAC robust estimator is used to obtain rigid transformations out of the resulting flow v ectors. T he i mages a re t ransformed into the same coordinate frame and overlapping areas are blended. The accuracy of the proposed stitching scheme is evaluated on two datasets of 7 and 4 OCT volumes, respectively. By placing the specimens on a high-accuracy motorized translational stage, ground truth transformations are available. This results in a mean translational error between two adjacent volumes of 16.6 ± 0.8 μm (2.8 ± 0.13 voxels). To the author’s knowledge, this is the first reported stitching of multiple 3D OCT volumes by using dense voxel information in the registration process. The achieved results are sufficient for providing high accuracy OCT panoramic images. Combined with a recently available high-speed 4D OCT, our method enables interactive stitching of hand-guided acquisitions.
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Hossain, Muhammad Shahadat, Milovan Urosevic, and Anton Kepic. "Volumetric interpretation of 3D hard rock seismic data." ASEG Extended Abstracts 2013, no. 1 (December 2013): 1–3. http://dx.doi.org/10.1071/aseg2013ab088.

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42

Robertson, Douglas D., Charles J. Sutherland, Brandon W. Chan, Jacqueline C. Hodge, William W. Scott, and Elliot K. Fishman. "Depiction of Pelvic Fractures Using 3D Volumetric Holography." Journal of Computer Assisted Tomography 19, no. 6 (November 1995): 967–74. http://dx.doi.org/10.1097/00004728-199511000-00024.

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Hassan, Hossam, Ayman El-Baz, Aly A. Farag, Allan G. Farman, D. Tasman, and William M. Miller. "A volumetric 3D model of the human jaw." International Congress Series 1281 (May 2005): 1244–49. http://dx.doi.org/10.1016/j.ics.2005.03.345.

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Chae, Michael P., David J. Hunter-Smith, Robert T. Spychal, and Warren Matthew Rozen. "3D volumetric analysis for planning breast reconstructive surgery." Breast Cancer Research and Treatment 146, no. 2 (June 18, 2014): 457–60. http://dx.doi.org/10.1007/s10549-014-3028-1.

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45

Wang, Chao, Yu-Shen Liu, Min Liu, Jun-Hai Yong, and Jean-Claude Paul. "Robust shape normalization of 3D articulated volumetric models." Computer-Aided Design 44, no. 12 (December 2012): 1253–68. http://dx.doi.org/10.1016/j.cad.2012.07.006.

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46

Del Grande, Filippo, Natalie Hinterholzer, and Daniel Nanz. "3D MRI: Technical Considerations and Practical Integration." Seminars in Musculoskeletal Radiology 25, no. 03 (June 2021): 381–87. http://dx.doi.org/10.1055/s-0041-1731059.

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AbstractOne of the main advantages of three-dimensional (3D) magnetic resonance imaging (MRI) is the possibility of isotropic voxels and reconstructed planar cuts through the volumetric data set in any orientation with multiplanar reformation software through real-time evaluation. For example, reformats by the radiologist during reporting allows exploitation of the full potential of isotropic 3D volumetric acquisition or through standardized retrospective reformats of thicker predefined slices of an isotropic volumetric data set by technologists. The main challenges for integrating 3D fast spin echo (FSE) and turbo spin-echo (TSE) MRI in clinical practice are a long acquisition time and some artifacts, whereas for integrating 3D gradient-recalled echo protocols, the main challenges are lower signal-to-noise ratios (SNRs) and the inability to produce intermediate, and T2-weighted contrast. The implementation of bidirectional parallel imaging acquisition and random undersampling acceleration strategies of 3D TSE pulse sequences substantially shortens the examination time with only minor SNR reductions. This article provides an overview of general technical considerations of 3D FSE and TSE sequences in musculoskeletal MRI. It also describes how these sequences achieve efficient data acquisition and reviews the main advantages and challenges for their introduction to clinical practice.
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47

Chopra, Satinder, and Kurt J. Marfurt. "Volumetric fault image enhancement — Some applications." Interpretation 5, no. 2 (May 31, 2017): T151—T161. http://dx.doi.org/10.1190/int-2016-0129.1.

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The interpretation of faults on 3D seismic data is often aided by the use of geometric attributes such as coherence and curvature. Unfortunately, these same attributes also delineate stratigraphic boundaries (geologic signal) and apparent discontinuities due to cross-cutting seismic noise. Effective fault mapping thus requires enhancing piecewise continuous faults and suppressing stratabound edges and unconformities as well as seismic noise. To achieve this objective, we apply two passes of edge-preserving structure-oriented filtering followed by a recently developed fault enhancement algorithm based on a directional Laplacian of a Gaussian operator. We determine the effectiveness of this workflow on a 3D seismic volume from central British Columbia, Canada.
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Sánchez Climent, Álvaro, and María Luisa Cerdeño Serrano. "Propuesta metodológica para el estudio volumétrico de cerámica arqueológica a través de programas free-software de edición 3D: el caso de las necrópolis celtibéricas del área meseteña." Virtual Archaeology Review 5, no. 11 (October 23, 2014): 20. http://dx.doi.org/10.4995/var.2014.4173.

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Nowadays the free-software programs have been converted into the ideal tools for the archaeological researches, reaching the same level as other commercial programs. For that reason, the 3D modeling tool Blender has reached in the last years a great popularity offering similar characteristics like other commercial 3D editing programs such as 3D Studio Max or AutoCAD. Recently, it has been developed the necessary script for the volumetric calculations of three-dimnesional objects, offering great possibilities to calculate the volume of the archaeological ceramics. In this paper, we present a methodological approach for the volumetric studies with Blender and a study case of funerary urns from several celtiberians cemeteries of the Spanish Meseta. The goal is to demonstrate the great possibilities that the 3D editing free-software tools have in the volumetric studies at the present time.
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Chen, He En, Han Wu He, and Zhi Yuan He. "A Maya Geometry Slices Generation Method for Volumetric 3D Display." Advanced Materials Research 314-316 (August 2011): 102–7. http://dx.doi.org/10.4028/www.scientific.net/amr.314-316.102.

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Volumetric 3D display system (alternatively known as true 3D display system) has recently seen great progress. Powerful and functional software that can interfaces with 3D display hardware system was eagerly expected. In this paper we propose a method of generating geometry slices that can be presented on Multi-planar 3D display which will be fused in the human visual system into a 3D volume. Our main novel contribution is to use the programming language of Maya – MEL (Maya Embedded Language) to obtain geometry slices or image slices that meet the projection requirements-- including spinning screen based projection and to and fro translating screen based projection. We show that set of cross-section slices with different thickness, interval angle or distance can be split from a built mechanical component. Moreover the experiments of assembling series of geometry slices together to form a 3D spatial object can be employed to simulate the performance of Multi-planar 3D display. The latest imaging method opens up many application areas when incorporating with a Volumetric 3D display which will enhance visualization of the complex structure , better appreciate the entire 3D data and improve product design, function visualization, manufacturing preview and maintenance training.
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Khalilzadeh, Omid, Laura M. Fayad, and Shivani Ahlawat. "3D MR Neurography." Seminars in Musculoskeletal Radiology 25, no. 03 (June 2021): 409–17. http://dx.doi.org/10.1055/s-0041-1730909.

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AbstractHigh-resolution isotropic volumetric three-dimensional (3D) magnetic resonance neurography (MRN) techniques enable multiplanar depiction of peripheral nerves. In addition, 3D MRN provides anatomical and functional tissue characterization of different disease conditions affecting the peripheral nerves. In this review article, we summarize clinically relevant technical considerations of 3D MRN image acquisition and review clinical applications of 3D MRN to assess peripheral nerve diseases, such as entrapments, trauma, inflammatory or infectious neuropathies, and neoplasms.
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