AIMC Journal:
IEEE transactions on medical imaging

Showing 441 to 450 of 687 articles

Partial Policy-Based Reinforcement Learning for Anatomical Landmark Localization in 3D Medical Images.

IEEE transactions on medical imaging Oct 9, 2019
Utilizing the idea of long-term cumulative return, reinforcement learning (RL) has shown remarkable performance in various fields. We follow the formulation of landmark localization in 3D medical images as an RL problem. Whereas value-based methods h...
Anatomic Landmarks Spine Aorta Tomography, X-Ray Computed Imaging, Three-Dimensional Magnetic Resonance Imaging Humans Machine Learning Algorithms
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DECT-MULTRA: Dual-Energy CT Image Decomposition With Learned Mixed Material Models and Efficient Clustering.

IEEE transactions on medical imaging Oct 8, 2019
Dual-energy computed tomography (DECT) imaging plays an important role in advanced imaging applications due to its material decomposition capability. Image-domain decomposition operates directly on CT images using linear matrix inversion, but the dec...
Least-Squares Analysis Head Phantoms, Imaging Humans Machine Learning Algorithms Tomography, X-Ray Computed Image Processing, Computer-Assisted Cluster Analysis
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Fetal Congenital Heart Disease Echocardiogram Screening Based on DGACNN: Adversarial One-Class Classification Combined with Video Transfer Learning.

IEEE transactions on medical imaging Oct 7, 2019
Fetal congenital heart disease (FHD) is a common and serious congenital malformation in children. In Asia, FHD birth defect rates have reached as high as 9.3%. For the early detection of birth defects and mortality, echocardiography remains the most ...
Humans Algorithms Pregnancy Deep Learning Video Recording Image Interpretation, Computer-Assisted Female Echocardiography Ultrasonography, Prenatal Heart Defects, Congenital
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DeepBranch: Deep Neural Networks for Branch Point Detection in Biomedical Images.

IEEE transactions on medical imaging Oct 7, 2019
Morphology reconstruction of tree-like structures in volumetric images, such as neurons, retinal blood vessels, and bronchi, is of fundamental interest for biomedical research. 3D branch points play an important role in many reconstruction applicatio...
Diagnostic Imaging Neurons Bronchi Retinal Vessels Algorithms Animals Image Processing, Computer-Assisted Humans Neural Networks, Computer
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Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening.

IEEE transactions on medical imaging Oct 7, 2019
We present a deep convolutional neural network for breast cancer screening exam classification, trained, and evaluated on over 200000 exams (over 1000000 images). Our network achieves an AUC of 0.895 in predicting the presence of cancer in the breast...
Humans Female Breast Neoplasms Radiologists Deep Learning Breast Image Interpretation, Computer-Assisted Early Detection of Cancer Mammography
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Missing MRI Pulse Sequence Synthesis Using Multi-Modal Generative Adversarial Network.

IEEE transactions on medical imaging Oct 4, 2019
Magnetic resonance imaging (MRI) is being increasingly utilized to assess, diagnose, and plan treatment for a variety of diseases. The ability to visualize tissue in varied contrasts in the form of MR pulse sequences in a single scan provides valuabl...
Humans Deep Learning Brain Image Processing, Computer-Assisted Magnetic Resonance Imaging
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Noise Adaptation Generative Adversarial Network for Medical Image Analysis.

IEEE transactions on medical imaging Sep 30, 2019
Machine learning has been widely used in medical image analysis under an assumption that the training and test data are under the same feature distributions. However, medical images from difference devices or the same device with different parameter ...
Muscle, Skeletal Tomography, Optical Coherence Bone and Bones Phantoms, Imaging Humans Machine Learning Deep Learning Ultrasonography Image Processing, Computer-Assisted
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Spatio-Temporal Convolutional LSTMs for Tumor Growth Prediction by Learning 4D Longitudinal Patient Data.

IEEE transactions on medical imaging Sep 25, 2019
Prognostic tumor growth modeling via volumetric medical imaging observations can potentially lead to better outcomes of tumor treatment management and surgical planning. Recent advances of convolutional networks (ConvNets) have demonstrated higher ac...
Adult Image Interpretation, Computer-Assisted Male Humans Middle Aged Neoplasms Machine Learning Neural Networks, Computer Imaging, Three-Dimensional Prognosis Models, Biological Female
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Automated Muscle Segmentation from Clinical CT Using Bayesian U-Net for Personalized Musculoskeletal Modeling.

IEEE transactions on medical imaging Sep 10, 2019
We propose a method for automatic segmentation of individual muscles from a clinical CT. The method uses Bayesian convolutional neural networks with the U-Net architecture, using Monte Carlo dropout that infers an uncertainty metric in addition to th...
Thigh Bayes Theorem Arthroplasty, Replacement, Hip Hip Patient-Specific Modeling Deep Learning Image Processing, Computer-Assisted Muscle, Skeletal Tomography, X-Ray Computed Female Male Humans Neural Networks, Computer
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Stacked Bidirectional Convolutional LSTMs for Deriving 3D Non-Contrast CT From Spatiotemporal 4D CT.

IEEE transactions on medical imaging Sep 2, 2019
The imaging workup in acute stroke can be simplified by deriving non-contrast CT (NCCT) from CT perfusion (CTP) images. This results in reduced workup time and radiation dose. To achieve this, we present a stacked bidirectional convolutional LSTM (C-...
Humans Stroke Male Perfusion Imaging Brain Middle Aged Four-Dimensional Computed Tomography Female Deep Learning Aged
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