Results 61 to 70 of about 412,052 (160)

Automatic Scan-to-BIM—The Impact of Semantic Segmentation Accuracy

Buildings
Scan-to-BIM is the process of converting point cloud data into a Building Information Model (BIM) that has proven essential for the AEC industry. Scan-to-BIM consists of two fundamental tasks—semantic segmentation and 3D reconstruction. Deep learning has
Jidnyasa Patil, Mohsen Kalantari
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LUNA: Loss-Construct Unsupervised Network Adjustment for Low-Dose CT Image Reconstruction

IEEE Access
Reconstructing low-dose CT imaging deals with handling the inherent noise within the data, which makes it a complex mathematical problem known as an ill-posed inverse problem.
Ritu Gothwal, Shailendra Tiwari, Shivendra Shivani   +2 more
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From Compressed-Sensing to Artificial Intelligence-Based Cardiac MRI Reconstruction

Frontiers in Cardiovascular Medicine, 2020
Cardiac magnetic resonance (CMR) imaging is an important tool for the non-invasive assessment of cardiovascular disease. However, CMR suffers from long acquisition times due to the need of obtaining images with high temporal and spatial resolution ...
Aurélien Bustin, Niccolo Fuin, René M. Botnar, René M. Botnar, Claudia Prieto, Claudia Prieto   +5 more
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Photoacoustic image reconstruction via deep learning [PDF]

Photons Plus Ultrasound: Imaging and Sensing 2018, 2018
Applying standard algorithms to sparse data problems in photoacoustic tomography (PAT) yields low-quality images containing severe under-sampling artifacts. To some extent, these artifacts can be reduced by iterative image reconstruction algorithms which allow to include prior knowledge such as smoothness, total variation (TV) or sparsity constraints ...
Antholzer, Stephan, Schwab, Johannes, Nuster, Robert, Haltmeier, Markus   +3 more
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Deep learning framework for digital breast tomosynthesis reconstruction [PDF]

Medical Imaging 2019: Physics of Medical Imaging, 2019
4 pages, 2 figures, submitted to ...
Moriakov, Nikita, Michielsen, Koen, Adler, Jonas, Mann, Ritse, Sechopoulos, Ioannis, Teuwen, Jonas   +5 more
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SynapseNet: Deep learning for automatic synapse reconstruction

Molecular Biology of the Cell
Electron microscopy is an important technique for the study of synaptic morphology and its relation to synaptic function. The data analysis for this task requires the segmentation of the relevant synaptic structures, such as synaptic vesicles (SV), active zones, mitochondria, presynaptic densities, synaptic ribbons, and synaptic compartments. Previous
Sarah Muth, Frederieke Moschref, Luca Freckmann, Sophia Mutschall, Ines Hojas-Garcia-Plaza, Julius N. Bahr, Arsen Petrovic, Thanh Thao Do, Valentin Schwarze, Anwai Archit, Kirsten Weyand, Susann Michanski, Lydia Maus, Cordelia Imig, Anika Hintze, Nils Brose, Carolin Wichmann, Ruben Fernandez-Busnadiego, Tobias Moser, Silvio O. Rizzoli, Benjamin H. Cooper, Constantin Pape   +21 more
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CryoEMNet driven symmetry-aware molecular reconstruction through deep learning enhanced electron microscopy

Scientific Reports
CryoEMNet introduces a symmetry-aware deep learning framework for molecular reconstruction in cryo-electron microscopy (cryo-EM), achieving high-resolution and structurally consistent 3D reconstructions.
Saksham Arora, Shin-Hung Pan, Sudhakar Kumar, Sunil K. Singh, Utkarsh Chauhan, Wadee Alhalabi, Varsha Arya, Bassma Saleh Alsulami, Ching-Hsien Hsu, Kwok Tai Chui, Brij B. Gupta   +10 more
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Image reconstruction of multispectral sparse sampling photoacoustic tomography based on deep algorithm unrolling

Photoacoustics
Photoacoustic tomography (PAT), as a novel medical imaging technology, provides structural, functional, and metabolism information of biological tissue in vivo.
Jia Ge, Zongxin Mo, Shuangyang Zhang, Xiaoming Zhang, Yutian Zhong, Zhaoyong Liang, Chaobin Hu, Wufan Chen, Li Qi   +8 more
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Survey of single image super‐resolution reconstruction

IET Image Processing, 2020
Image super‐resolution reconstruction refers to a technique of recovering a high‐resolution (HR) image (or multiple images) from a low‐resolution (LR) degraded image (or multiple images).
Kai Li, Shenghao Yang, Runting Dong, Xiaoying Wang, Jianqiang Huang   +4 more
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Scale-equivariant deep model-based optoacoustic image reconstruction

Photoacoustics
Model-based reconstruction provides state-of-the-art image quality for multispectral optoacoustic tomography. However, optimal regularization of in vivo data necessitates scan-specific adjustments of the regularization strength to compensate for ...
Christoph Dehner, Ledia Lilaj, Vasilis Ntziachristos, Guillaume Zahnd, Dominik Jüstel   +4 more
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