AIMC Journal:
IEEE transactions on medical imaging

Showing 471 to 480 of 687 articles

Use of a Tracer-Specific Deep Artificial Neural Net to Denoise Dynamic PET Images.

IEEE transactions on medical imaging Jul 5, 2019
Application of kinetic modeling (KM) on a voxel level in dynamic PET images frequently suffers from high levels of noise, drastically reducing the precision of parametric image analysis. In this paper, we investigate the use of machine learning and a...
Positron-Emission Tomography Phantoms, Imaging Raclopride Brain Image Processing, Computer-Assisted Humans Neural Networks, Computer Machine Learning
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k -Space Deep Learning for Accelerated MRI.

IEEE transactions on medical imaging Jul 5, 2019
The annihilating filter-based low-rank Hankel matrix approach (ALOHA) is one of the state-of-the-art compressed sensing approaches that directly interpolates the missing k -space data using low-rank Hankel matrix completion. The success of ALOHA is d...
Deep Learning Image Processing, Computer-Assisted Magnetic Resonance Imaging Humans Algorithms Brain
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CT Super-Resolution GAN Constrained by the Identical, Residual, and Cycle Learning Ensemble (GAN-CIRCLE).

IEEE transactions on medical imaging Jun 14, 2019
In this paper, we present a semi-supervised deep learning approach to accurately recover high-resolution (HR) CT images from low-resolution (LR) counterparts. Specifically, with the generative adversarial network (GAN) as the building block, we enfor...
Neural Networks, Computer Tomography, X-Ray Computed Female Humans Deep Learning Image Processing, Computer-Assisted Abdomen Aged Aged, 80 and over Male Tibia
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A Partially-Learned Algorithm for Joint Photo-acoustic Reconstruction and Segmentation.

IEEE transactions on medical imaging Jun 10, 2019
In an inhomogeneously illuminated photoacoustic image, important information like vascular geometry is not readily available, when only the initial pressure is reconstructed. To obtain the desired information, algorithms for image segmentation are of...
Photoacoustic Techniques Algorithms Neural Networks, Computer Tomography Image Processing, Computer-Assisted Phantoms, Imaging
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Exploiting Epistemic Uncertainty of Anatomy Segmentation for Anomaly Detection in Retinal OCT.

IEEE transactions on medical imaging May 31, 2019
Diagnosis and treatment guidance are aided by detecting relevant biomarkers in medical images. Although supervised deep learning can perform accurate segmentation of pathological areas, it is limited by requiring a priori definitions of these regions...
Supervised Machine Learning Image Processing, Computer-Assisted Humans Artifacts Tomography, Optical Coherence Retina Algorithms
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Automated Classification of Apoptosis in Phase Contrast Microscopy Using Capsule Network.

IEEE transactions on medical imaging May 22, 2019
Automatic and accurate classification of apoptosis, or programmed cell death, will facilitate cell biology research. The state-of-the-art approaches in apoptosis classification use deep convolutional neural networks (CNNs). However, these networks ar...
Cytological Techniques Humans Image Processing, Computer-Assisted Cells Neural Networks, Computer Apoptosis Microscopy, Phase-Contrast Cell Line, Tumor
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Adaptive Feature Recombination and Recalibration for Semantic Segmentation With Fully Convolutional Networks.

IEEE transactions on medical imaging May 20, 2019
Fully convolutional networks have been achieving remarkable results in image semantic segmentation, while being efficient. Such efficiency results from the capability of segmenting several voxels in a single forward pass. So, there is a direct spatia...
Semantics Magnetic Resonance Imaging Stroke Brain Neoplasms Humans Deep Learning Neural Networks, Computer Image Processing, Computer-Assisted Brain
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Domain Progressive 3D Residual Convolution Network to Improve Low-Dose CT Imaging.

IEEE transactions on medical imaging May 17, 2019
The wide applications of X-ray computed tomography (CT) bring low-dose CT (LDCT) into a clinical prerequisite, but reducing the radiation exposure in CT often leads to significantly increased noise and artifacts, which might lower the judgment accura...
Tomography, X-Ray Computed Deep Learning Imaging, Three-Dimensional Abdomen Artifacts Humans Algorithms Thorax Phantoms, Imaging
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nCREANN: Nonlinear Causal Relationship Estimation by Artificial Neural Network; Applied for Autism Connectivity Study.

IEEE transactions on medical imaging May 13, 2019
Quantifying causal (effective) interactions between different brain regions are very important in neuroscience research. Many conventional methods estimate effective connectivity based on linear models. However, using linear connectivity models may o...
Brain Computer Simulation Nerve Net Child Electroencephalography Signal Processing, Computer-Assisted Humans Nonlinear Dynamics Neural Networks, Computer Autism Spectrum Disorder
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Adaptive Augmentation of Medical Data Using Independently Conditional Variational Auto-Encoders.

IEEE transactions on medical imaging May 6, 2019
Current deep supervised learning methods typically require large amounts of labeled data for training. Since there is a significant cost associated with clinical data acquisition and labeling, medical datasets used for training these models are relat...
Image Interpretation, Computer-Assisted Neoplasms Deep Learning Ultrasonography Magnetic Resonance Imaging Spine Algorithms Databases, Factual Brain Humans
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