AIMC Journal:
IEEE transactions on medical imaging

Showing 311 to 320 of 687 articles

Automatic Inter-Frame Patient Motion Correction for Dynamic Cardiac PET Using Deep Learning.

IEEE transactions on medical imaging Nov 30, 2021
Patient motion during dynamic PET imaging can induce errors in myocardial blood flow (MBF) estimation. Motion correction for dynamic cardiac PET is challenging because the rapid tracer kinetics of 82Rb leads to substantial tracer distribution change ...
Humans Deep Learning Image Processing, Computer-Assisted Motion Positron-Emission Tomography Movement
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Deep Interactive Denoiser (DID) for X-Ray Computed Tomography.

IEEE transactions on medical imaging Oct 27, 2021
Low-dose computed tomography (LDCT) is desirable for both diagnostic imaging and image-guided interventions. Denoisers are widely used to improve the quality of LDCT. Deep learning (DL)-based denoisers have shown state-of-the-art performance and are ...
Tomography, X-Ray Computed Deep Learning Image Processing, Computer-Assisted
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Patch-Based U-Net Model for Isotropic Quantitative Differential Phase Contrast Imaging.

IEEE transactions on medical imaging Oct 27, 2021
Quantitative differential phase-contrast (qDPC) imaging is a label-free phase retrieval method for weak phase objects using asymmetric illumination. However, qDPC imaging with fewer intensity measurements leads to anisotropic phase distribution in re...
Neural Networks, Computer Image Processing, Computer-Assisted Microscopy, Phase-Contrast
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Unpaired MR Motion Artifact Deep Learning Using Outlier-Rejecting Bootstrap Aggregation.

IEEE transactions on medical imaging Oct 27, 2021
Recently, deep learning approaches for MR motion artifact correction have been extensively studied. Although these approaches have shown high performance and lower computational complexity compared to classical methods, most of them require supervise...
Deep Learning Image Processing, Computer-Assisted Magnetic Resonance Imaging Motion Artifacts
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Deep Learning for Ultrasound Beamforming in Flexible Array Transducer.

IEEE transactions on medical imaging Oct 27, 2021
Ultrasound imaging has been developed for image-guided radiotherapy for tumor tracking, and the flexible array transducer is a promising tool for this task. It can reduce the user dependence and anatomical changes caused by the traditional ultrasound...
Deep Learning Ultrasonography Image Processing, Computer-Assisted Phantoms, Imaging Transducers
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Downsampled Imaging Geometric Modeling for Accurate CT Reconstruction via Deep Learning.

IEEE transactions on medical imaging Oct 27, 2021
X-ray computed tomography (CT) is widely used clinically to diagnose a variety of diseases by reconstructing the tomographic images of a living subject using penetrating X-rays. For accurate CT image reconstruction, a precise imaging geometric model ...
Humans Neural Networks, Computer Algorithms Tomography, X-Ray Computed Deep Learning Image Processing, Computer-Assisted
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Guest Editorial Annotation-Efficient Deep Learning: The Holy Grail of Medical Imaging.

IEEE transactions on medical imaging Sep 30, 2021
Deep Learning Radiography Diagnostic Imaging
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Interpretability-Driven Sample Selection Using Self Supervised Learning for Disease Classification and Segmentation.

IEEE transactions on medical imaging Sep 30, 2021
In supervised learning for medical image analysis, sample selection methodologies are fundamental to attain optimum system performance promptly and with minimal expert interactions (e.g. label querying in an active learning setup). In this article we...
Lung Supervised Machine Learning Uncertainty
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Interactive Few-Shot Learning: Limited Supervision, Better Medical Image Segmentation.

IEEE transactions on medical imaging Sep 30, 2021
Many known supervised deep learning methods for medical image segmentation suffer an expensive burden of data annotation for model training. Recently, few-shot segmentation methods were proposed to alleviate this burden, but such methods often showed...
Algorithms Deep Learning Simulation Training
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IFSS-Net: Interactive Few-Shot Siamese Network for Faster Muscle Segmentation and Propagation in Volumetric Ultrasound.

IEEE transactions on medical imaging Sep 30, 2021
We present an accurate, fast and efficient method for segmentation and muscle mask propagation in 3D freehand ultrasound data, towards accurate volume quantification. A deep Siamese 3D Encoder-Decoder network that captures the evolution of the muscle...
Humans Neural Networks, Computer Tomography, X-Ray Computed Ultrasonography Image Processing, Computer-Assisted Muscles
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