AIMC Journal:
IEEE transactions on medical imaging

Showing 661 to 670 of 699 articles

Inf-Net: Automatic COVID-19 Lung Infection Segmentation From CT Images.

IEEE transactions on medical imaging Aug 1, 2020
Coronavirus Disease 2019 (COVID-19) spread globally in early 2020, causing the world to face an existential health crisis. Automated detection of lung infections from computed tomography (CT) images offers a great potential to augment the traditional...
Coronavirus Infections Betacoronavirus Pneumonia, Viral SARS-CoV-2 Lung Supervised Machine Learning COVID-19 Algorithms Tomography, X-Ray Computed Humans Pandemics
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Dual-Sampling Attention Network for Diagnosis of COVID-19 From Community Acquired Pneumonia.

IEEE transactions on medical imaging Aug 1, 2020
The coronavirus disease (COVID-19) is rapidly spreading all over the world, and has infected more than 1,436,000 people in more than 200 countries and territories as of April 9, 2020. Detecting COVID-19 at early stage is essential to deliver proper h...
Deep Learning ROC Curve Coronavirus Infections Algorithms Tomography, X-Ray Computed SARS-CoV-2 Betacoronavirus Pneumonia, Viral Image Interpretation, Computer-Assisted Radiography, Thoracic Community-Acquired Infections Humans Pandemics COVID-19
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Accurate Screening of COVID-19 Using Attention-Based Deep 3D Multiple Instance Learning.

IEEE transactions on medical imaging Aug 1, 2020
Automated Screening of COVID-19 from chest CT is of emergency and importance during the outbreak of SARS-CoV-2 worldwide in 2020. However, accurate screening of COVID-19 is still a massive challenge due to the spatial complexity of 3D volumes, the la...
Humans Pandemics Imaging, Three-Dimensional Coronavirus Infections Radiography, Thoracic Betacoronavirus Pneumonia, Viral COVID-19 SARS-CoV-2 Algorithms Lung Tomography, X-Ray Computed Deep Learning
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Prior-Attention Residual Learning for More Discriminative COVID-19 Screening in CT Images.

IEEE transactions on medical imaging Aug 1, 2020
We propose a conceptually simple framework for fast COVID-19 screening in 3D chest CT images. The framework can efficiently predict whether or not a CT scan contains pneumonia while simultaneously identifying pneumonia types between COVID-19 and Inte...
SARS-CoV-2 Adult Middle Aged Pandemics COVID-19 Humans Tomography, X-Ray Computed Coronavirus Infections Lung Betacoronavirus Radiography, Thoracic Deep Learning Imaging, Three-Dimensional Pneumonia, Viral
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Breast Cancer Diagnosis in Digital Breast Tomosynthesis: Effects of Training Sample Size on Multi-Stage Transfer Learning Using Deep Neural Nets.

IEEE transactions on medical imaging Mar 1, 2019
In this paper, we developed a deep convolutional neural network (CNN) for the classification of malignant and benign masses in digital breast tomosynthesis (DBT) using a multi-stage transfer learning approach that utilized data from similar auxiliary...
Breast Neoplasms Humans Mammography Neural Networks, Computer Sample Size Area Under Curve Machine Learning Michigan
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Recalibrating Fully Convolutional Networks With Spatial and Channel "Squeeze and Excitation" Blocks.

IEEE transactions on medical imaging Feb 1, 2019
In a wide range of semantic segmentation tasks, fully convolutional neural networks (F-CNNs) have been successfully leveraged to achieve the state-of-the-art performance. Architectural innovations of F-CNNs have mainly been on improving spatial encod...
Humans Image Processing, Computer-Assisted Diagnostic Imaging Neural Networks, Computer Retina Databases, Factual Brain
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Fully Automatic Left Atrium Segmentation From Late Gadolinium Enhanced Magnetic Resonance Imaging Using a Dual Fully Convolutional Neural Network.

IEEE transactions on medical imaging Feb 1, 2019
Atrial fibrillation (AF) is the most prevalent form of cardiac arrhythmia. Current treatments for AF remain suboptimal due to a lack of understanding of the underlying atrial structures that directly sustain AF. Existing approaches for analyzing atri...
Heart Atria Gadolinium Imaging, Three-Dimensional Magnetic Resonance Imaging Atrial Fibrillation Humans Neural Networks, Computer Algorithms
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Segmentation of Nuclei in Histopathology Images by Deep Regression of the Distance Map.

IEEE transactions on medical imaging Feb 1, 2019
The advent of digital pathology provides us with the challenging opportunity to automatically analyze whole slides of diseased tissue in order to derive quantitative profiles that can be used for diagnosis and prognosis tasks. In particular, for the ...
Humans Databases, Factual Neoplasms Deep Learning Image Interpretation, Computer-Assisted Cell Nucleus Histological Techniques
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Joint Optic Disc and Cup Segmentation Based on Multi-Label Deep Network and Polar Transformation.

IEEE transactions on medical imaging Jul 1, 2018
Glaucoma is a chronic eye disease that leads to irreversible vision loss. The cup to disc ratio (CDR) plays an important role in the screening and diagnosis of glaucoma. Thus, the accurate and automatic segmentation of optic disc (OD) and optic cup (...
Diagnostic Techniques, Ophthalmological Humans Deep Learning Glaucoma Image Interpretation, Computer-Assisted Databases, Factual Optic Disk
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Interactive Medical Image Segmentation Using Deep Learning With Image-Specific Fine Tuning.

IEEE transactions on medical imaging Jul 1, 2018
Convolutional neural networks (CNNs) have achieved state-of-the-art performance for automatic medical image segmentation. However, they have not demonstrated sufficiently accurate and robust results for clinical use. In addition, they are limited by ...
Fetus Prenatal Diagnosis Humans Brain Deep Learning Pregnancy Magnetic Resonance Imaging Female Image Interpretation, Computer-Assisted Brain Neoplasms
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