AIMC Topic: Tomography

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Identification of non-activated lymphocytes using three-dimensional refractive index tomography and machine learning.

Scientific reports Jul 27, 2017
Identification of lymphocyte cell types are crucial for understanding their pathophysiological roles in human diseases. Current methods for discriminating lymphocyte cell types primarily rely on labelling techniques with magnetic beads or fluorescenc...
Refractometry Tomography Mice Mice, Inbred C57BL Lymphocytes Lymphocyte Activation Single-Cell Analysis Machine Learning Animals
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On the influence of spread constant in radial basis networks for electrical impedance tomography.

Physiological measurement May 20, 2016
Electrical impedance tomography (EIT) is a non-invasive imaging technique. The main task of this work is to solve a non-linear inverse problem, for which several techniques have been suggested, but none of which gives a very high degree of accuracy. ...
Neural Networks, Computer Computer Simulation Image Processing, Computer-Assisted Tomography Electric Impedance Phantoms, Imaging
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Tactile soft-sparse mean fluid-flow imaging with a robotic whisker array.

Bioinspiration & biomimetics Aug 4, 2015
An array of whiskers is critical to many mammals to survive in their environment. However, current engineered systems generally employ vision, radar or sonar to explore the surroundings, not having sufficiently benefited from tactile perception. Insp...
Tomography Vibrissae Biomimetics Environmental Monitoring Rheology Robotics Touch Equipment Design Transducers, Pressure Humans Equipment Failure Analysis Animals
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Supervised and unsupervised learning for lung perfusion data segmentation in electrical impedance tomography.

Biomedical physics & engineering express Jun 13, 2025
: Effective lung gas exchange relies on the balance between alveolar ventilation and perfusion, which can be disrupted in mechanically ventilated patients. Lung perfusion assessment using electrical impedance tomography (EIT) typically involves a sud...
Algorithms Animals Neural Networks, Computer Image Processing, Computer-Assisted Support Vector Machine Unsupervised Machine Learning Lung Swine Electric Impedance Acute Lung Injury Tomography Supervised Machine Learning Perfusion
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[Image reconstruction for cerebral hemorrhage based on improved densely-connected fully convolutional neural network].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi Dec 25, 2024
Cerebral hemorrhage is a serious cerebrovascular disease with high morbidity and high mortality, for which timely diagnosis and treatment are crucial. Electrical impedance tomography (EIT) is a functional imaging technique which is able to detect abn...
Humans Neural Networks, Computer Phantoms, Imaging Tomography Image Processing, Computer-Assisted Cerebral Hemorrhage Electric Impedance Brain Convolutional Neural Networks
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FMT-ReconNet: Fluorescence Molecular Tomography Reconstruction using Prior Knowledge and Deformation Neural Network.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
Fluorescence molecular tomography (FMT) is a powerful imaging technique for 3D reconstruction of internal fluorescent sources. However, its spatial resolution is limited by a simplified forward model and an ill-posed inverse problem. To address this,...
Algorithms Fluorescence Imaging, Three-Dimensional Humans Neural Networks, Computer Tomography Image Processing, Computer-Assisted Tomography, Optical
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[Research of electrical impedance tomography based on multilayer artificial neural network optimized by Hadamard product for human-chest models].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi Jun 25, 2024
Electrical impedance tomography (EIT) is a non-radiation, non-invasive visual diagnostic technique. In order to improve the imaging resolution and the removing artifacts capability of the reconstruction algorithms for electrical impedance imaging in ...
Lung Image Processing, Computer-Assisted Thorax Tomography Electric Impedance Humans Neural Networks, Computer Algorithms
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Quantifying Fibrosis in Fibrotic Lung Disease: A Good Human Plus a Machine Is the Best Combination?

Annals of the American Thoracic Society Feb 1, 2024
Lung Diseases, Interstitial Tomography Deep Learning Fibrosis Humans
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Structure-fused deep 3D hierarchical network: A bioluminescence tomography scheme for different imaging objects.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2023
Monte Carlo eXtreme (MCX) method has a unique advantage for deep neural network based bioluminescence tomography (BLT) reconstruction. However, this method ignores the distribution of sources energy and relies on the determined tissue structure. In t...
Monte Carlo Method Phantoms, Imaging Neural Networks, Computer Tomography
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Deep learning based reconstruction enables high-resolution electrical impedance tomography for lung function assessment.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2023
Recently, deep learning based methods have shown potential as alternative approaches for lung time difference electrical impedance tomography (tdEIT) reconstruction other than traditional regularized least square methods, that have inherent severe il...
Electric Impedance Tomography Tomography, X-Ray Computed Lung Deep Learning Humans
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