1st and 2nd FM generation 3D halftoning1 MICRON PIXELS133-MEGAPIXEL180 degree images1-bit matrix completion1/f noise108 Megapixel100 Hue test
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2.5D reconstruction2D VIEWS2D DCT2D to Hologram conversion2-d scale2D metrics2D and 3D video2D-plus-depth video2.5 D printing2D/3D imaging, high performance computing, imaging systems, efficient computations and storage2.5D PRINTING2.5D printing2D AND 3D CONVERTIBLE DISPLAY2.5D2D2AFC2-D barcodes2D-TO-3D CONVERSION ARTIFACTS2D printing
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3D model3D compression3D Imaging3D TRANSFORMATION360-degree Image3D surface reproduction3D Range Data3D Modeling3D STACK3D Video Communications3D Shape Indexing and Retrieval3D/4D DATA PROCESSING AND FILTERING360-degree videos3D connected tube model3D scene flow estimation3D Tracking3D EDUCATIONAL MATERIAL3D Digital Image Correlation3D image compression3D-HEVC3D adaptive halftoning3D Halftoning3D Data Sources3D camera3D Communications360-degree content3D printing3D shape3D PRINTER3D Mapping3D scanning3D capture3D modelling360 degree images3D Range Data Compression3D Point Cloud3D affine transformation3D recovery3D Printing3D modeling3D/2D Visuals3D digital halftoning3D Vision3D Immersion3D rigid transformations3D RECONSTRUCTION360 IMAGING3D HALFTONING3D depth sensing3D range scanning3D Curvelet3ARRI footage360° video3D mesh3D shape indexing and retrieval3D refinement3D-color perception3D display3D Measurement3D theater program listing3D Data Processing3D Telepresence3D DIGITIZATION METHOD FOR OIL PAINTINGS3D position measurement of people3D-shooting3D Object Detection360-degree images3D Morphable Model3D face alignment3D PRINTING3D MODEL3D video3D-LUT3D/4D Scanning3D stereo vision360 panorama3D perception3D CAMERAS360 degrees video360-degree art exhibition360-degree image projection3D mapping and localization3D/4D Data Processing and Filtering360VR360-degree video streaming3D depth-map360-video3D Saliency3D surface3D data processing3D optical scans3D scene classification3D video processing3D warping3D objects360-degree3D MESHES3D Display3D Gaussian splatting3DSR3D displays360-degree video3D communications3DViewers360° STEREO PANORAMAS3D Iterative Halftoning3D MESH3D-CNN3D Lidar3D Scene Reconstruction3D VISUALIZATION3D Compression and Encryption3DMM3D reconstruction3D SALIENCY3D Meshes3D print3D halftoning3D recursive search3D-human body detection3-T pixel3D Video3D SCENE RECONSTRUCTION AND MODELING3D and 2D3D SHAPE INDEXING AND RETRIEVAL3D Quality3D Video Conferencing3D shape analysis360-DEGREE IMAGE360-deg quality assessment3d localization3D MODELLING3-D RECONSTRUCTION3D RANGE IMAGING3D Image Processing3D object shape3D Computer Graphics3D Compression3D Models3D point cloud3D human-centered technologies3D Scene Reconstruction and Modeling3DCNN3D-Anisotropic smoothing3D projector3D mesh simplification35MM FILM DIGITIZATION3D localization3D/4D SCANNING3D-assisted features3D localization and mapping3D digitization and dissemination3D colour Digital Image Correlation3D Print Appearance3D range geometry3D RECOVERY3D printer360° VIDEO3D INTERACTION3D ACQUISITION ARCHITECTURE3D audio3D imaging360 Video3A ALGORITHMS360x3D scene capture3-D SHAPE RECOVERY3d mapping3D DISPLAY3D-high efficiency video coding3D visual representation3D USER INTERFACES3D PROFILE360-Degree Video Technology3D cinema and TV3D TV360-degree imaging3D Color Printing3D Reconstruction3D-printing3D Range Data Encoding3d3D IMAGE3d video3D STIMULI3D glasses3D COMPRESSION AND ENCRYPTION3D surface structure based halftoning3D vision3D encoding3D
Muralikrishnan Gopalakrishnan Meena, Amir K. Ziabari, Singanallur V. Venkatakrishnan, Isaac R. Lyngaas, Matthew R. Norman, Balint Joo, Thomas L. Beck, Charles A. Bouman, Anuj J. Kapadia, Xiao Wang
We introduce a physics guided data-driven method for image-based multi-material decomposition for dual-energy computed tomography (CT) scans. The method is demonstrated for CT scans of virtual human phantoms containing more than two types of tissues. The method is a physics-driven supervised learning technique. We take advantage of the mass attenuation coefficient of dense materials compared to that of muscle tissues to perform a preliminary extraction of the dense material from the images using unsupervised methods. We then perform supervised deep learning on the images processed by the extracted dense material to obtain the final multi-material tissue map. The method is demonstrated on simulated breast models with calcifications as the dense material placed amongst the muscle tissues. The physics-guided machine learning method accurately decomposes the various tissues from input images, achieving a normalized root-mean-squared error of 2.75%.