AIMC Journal:
IEEE transactions on medical imaging

Showing 291 to 300 of 687 articles

Graph-Based Region and Boundary Aggregation for Biomedical Image Segmentation.

IEEE transactions on medical imaging Mar 2, 2022
Segmentation is a fundamental task in biomedical image analysis. Unlike the existing region-based dense pixel classification methods or boundary-based polygon regression methods, we build a novel graph neural network (GNN) based deep learning framewo...
Optic Disk Fundus Oculi Semantics Image Processing, Computer-Assisted Neural Networks, Computer
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Learning With Privileged Multimodal Knowledge for Unimodal Segmentation.

IEEE transactions on medical imaging Mar 2, 2022
Multimodal learning usually requires a complete set of modalities during inference to maintain performance. Although training data can be well-prepared with high-quality multiple modalities, in many cases of clinical practice, only one modality can b...
Heart Neural Networks, Computer Humans
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Multitask Deep Learning Reconstruction and Localization of Lesions in Limited Angle Diffuse Optical Tomography.

IEEE transactions on medical imaging Mar 2, 2022
Diffuse optical tomography (DOT) leverages near-infrared light propagation through tissue to assess its optical properties and identify abnormalities. DOT image reconstruction is an ill-posed problem due to the highly scattered photons in the medium ...
Algorithms Artifacts Tomography, Optical Image Processing, Computer-Assisted Deep Learning
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Predicting Embryo Viability Based on Self-Supervised Alignment of Time-Lapse Videos.

IEEE transactions on medical imaging Feb 2, 2022
With self-supervised learning, both labeled and unlabeled data can be used for representation learning and model pretraining. This is particularly relevant when automating the selection of a patient's fertilized eggs (embryos) during a fertility trea...
Female ROC Curve Pregnancy Time-Lapse Imaging Humans Probability Supervised Machine Learning
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DIFFnet: Diffusion Parameter Mapping Network Generalized for Input Diffusion Gradient Schemes and b-Value.

IEEE transactions on medical imaging Feb 2, 2022
In MRI, deep neural networks have been proposed to reconstruct diffusion model parameters. However, the inputs of the networks were designed for a specific diffusion gradient scheme (i.e., diffusion gradient directions and numbers) and a specific b-v...
Neurites Diffusion Magnetic Resonance Imaging Diffusion Tensor Imaging Brain Magnetic Resonance Imaging Humans Neural Networks, Computer
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SMU-Net: Saliency-Guided Morphology-Aware U-Net for Breast Lesion Segmentation in Ultrasound Image.

IEEE transactions on medical imaging Feb 2, 2022
Deep learning methods, especially convolutional neural networks, have been successfully applied to lesion segmentation in breast ultrasound (BUS) images. However, pattern complexity and intensity similarity between the surrounding tissues (i.e., back...
Image Processing, Computer-Assisted Ultrasonography Neural Networks, Computer Female Humans Ultrasonography, Mammary
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Propagating Uncertainty Across Cascaded Medical Imaging Tasks for Improved Deep Learning Inference.

IEEE transactions on medical imaging Feb 2, 2022
Although deep networks have been shown to perform very well on a variety of medical imaging tasks, inference in the presence of pathology presents several challenges to common models. These challenges impede the integration of deep learning models in...
Magnetic Resonance Imaging Humans Uncertainty Deep Learning Image Processing, Computer-Assisted Brain Neoplasms
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Adaptive Hierarchical Dual Consistency for Semi-Supervised Left Atrium Segmentation on Cross-Domain Data.

IEEE transactions on medical imaging Feb 2, 2022
Semi-supervised learning provides great significance in left atrium (LA) segmentation model learning with insufficient labelled data. Generalising semi-supervised learning to cross-domain data is of high importance to further improve model robustness...
Supervised Machine Learning Heart Atria Contrast Media Gadolinium Deep Learning
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Genetic U-Net: Automatically Designed Deep Networks for Retinal Vessel Segmentation Using a Genetic Algorithm.

IEEE transactions on medical imaging Feb 2, 2022
Recently, many methods based on hand-designed convolutional neural networks (CNNs) have achieved promising results in automatic retinal vessel segmentation. However, these CNNs remain constrained in capturing retinal vessels in complex fundus images....
Image Processing, Computer-Assisted Fundus Oculi Neural Networks, Computer Retinal Vessels
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Global-Local Transformer for Brain Age Estimation.

IEEE transactions on medical imaging Dec 30, 2021
Deep learning can provide rapid brain age estimation based on brain magnetic resonance imaging (MRI). However, most studies use one neural network to extract the global information from the whole input image, ignoring the local fine-grained details. ...
Magnetic Resonance Imaging Neuroimaging Neural Networks, Computer Software Brain
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