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Showing 761 to 770 of 1686 articles

Learning Cellular Phenotypes through Supervision.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Nov 1, 2021
Image-based cell phenotyping is an important and open problem in computational pathology. The two principal challenges are: 1) making the cell cluster properties insensitive to experimental settings (like seed point and feature selection) and 2) ensu...
Phenotype Learning Supervised Machine Learning
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Anatomical Landmark Detection using Deep Appearance-Context Network.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Nov 1, 2021
Accurate identification of anatomical landmarks is a crucial step in medical image analysis. While deep neural networks have shown impressive performance on computer vision tasks, they rely on a large amount of data, which is often not available. In ...
Neural Networks, Computer Radiography Cephalometry Spine
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Deep-ReAP: Deep Representations And Partial label learning for Multi-pathology Classification.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Nov 1, 2021
Automated detection of pathology in images with multiple pathologies is one of the most challenging problems in medical diagnostics. The primary hurdles for automated systems include data imbalance across pathology categories and structural variation...
Humans Deep Learning Pathology
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Forward Model and Deep Learning Based Iterative Deconvolution for Robust Dynamic CT Perfusion.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Nov 1, 2021
Perfusion maps obtained from low-dose computed tomography (CT) data suffer from poor signal to noise ratio. To enhance the quality of the perfusion maps, several works rely on denoising the low-dose CT (LD-CT) images followed by conventional regulari...
Neural Networks, Computer Tomography, X-Ray Computed Deep Learning Perfusion Signal-To-Noise Ratio
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A Novel Adaptive Fuzzy Deep Learning Approach for Histopathologic Cancer Detection.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Nov 1, 2021
We proposed a novel model that integrates the fuzzy theory and group equivariant convolutional neural network for histopathologic cancer detection. The proposed fuzzy group equivariant convolutional neural network consists of the convolutional networ...
Humans Neural Networks, Computer Neoplasms Deep Learning
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Blind microscopy image denoising with a deep residual and multiscale encoder/decoder network.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Nov 1, 2021
In computer-aided diagnosis (CAD) focused on microscopy, denoising improves the quality of image analysis. In general, the accuracy of this process may depend both on the experience of the microscopist and on the equipment sensitivity and specificity...
Neural Networks, Computer Sensitivity and Specificity Diagnosis, Computer-Assisted Image Processing, Computer-Assisted Microscopy
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A CNN and LSTM Network for Eye-Blink Classification from MRI Scanner Monitoring Videos.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Nov 1, 2021
Eye closure changes brain activity, so eye-blink tracking of subjects undergoing resting-state functional magnetic resonance imaging (fMRI) is relevant for identifying when a subject blinks, falls asleep, or keeps their eyes closed. Existing MRI eye-...
Humans Neural Networks, Computer Prospective Studies Brain Magnetic Resonance Imaging Brain Mapping
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Multi-modal Broad Learning System for Medical Image and Text-based Classification.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Nov 1, 2021
Automatic classification of medical images plays an essential role in computer-aided diagnosis. However, the medical images arise from the small number of available data and the improvement of existing data-enhancement methods are limited. In order t...
Diagnosis, Computer-Assisted Deep Learning
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Learning to Generate Missing Pulse Sequence in MRI using Deep Convolution Neural Network Trained with Visual Turing Test.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Nov 1, 2021
Magnetic resonance imaging (MRI) is widely used in clinical applications due to its ability to acquire a wide variety of soft tissues using multiple pulse sequences. Each sequence provides information that generally complements the other. However, fa...
Neural Networks, Computer Brain Image Processing, Computer-Assisted Magnetic Resonance Imaging Signal-To-Noise Ratio
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Hierarchical Consistency Regularized Mean Teacher for Semi-supervised 3D Left Atrium Segmentation.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Nov 1, 2021
Deep learning has achieved promising segmentation performance on 3D left atrium MR images. However, annotations for segmentation tasks are expensive, costly and difficult to obtain. In this paper, we introduce a novel hierarchical consistency regular...
Humans Students Imaging, Three-Dimensional Supervised Machine Learning Heart Atria
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