AIMC Journal:
Medical image analysis

Showing 421 to 430 of 684 articles

Deep pyramid local attention neural network for cardiac structure segmentation in two-dimensional echocardiography.

Medical image analysis Oct 18, 2020
Automatic semantic segmentation in 2D echocardiography is vital in clinical practice for assessing various cardiac functions and improving the diagnosis of cardiac diseases. However, two distinct problems have persisted in automatic segmentation in 2...
Heart Attention Echocardiography Ultrasonography Neural Networks, Computer Humans
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AI-driven quantification, staging and outcome prediction of COVID-19 pneumonia.

Medical image analysis Oct 15, 2020
Coronavirus disease 2019 (COVID-19) emerged in 2019 and disseminated around the world rapidly. Computed tomography (CT) imaging has been proven to be an important tool for screening, disease quantification and staging. The latter is of extreme import...
Triage Radiographic Image Interpretation, Computer-Assisted Disease Progression Pneumonia, Viral Humans Prognosis SARS-CoV-2 Neural Networks, Computer Artificial Intelligence COVID-19 Biomarkers
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Reducing annotation effort in digital pathology: A Co-Representation learning framework for classification tasks.

Medical image analysis Oct 9, 2020
Classification of digital pathology images is imperative in cancer diagnosis and prognosis. Recent advancements in deep learning and computer vision have greatly benefited the pathology workflow by developing automated solutions for classification ta...
Deep Learning Workflow Humans Neural Networks, Computer
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Machine-learning-based multiple abnormality prediction with large-scale chest computed tomography volumes.

Medical image analysis Oct 9, 2020
Machine learning models for radiology benefit from large-scale data sets with high quality labels for abnormalities. We curated and analyzed a chest computed tomography (CT) data set of 36,316 volumes from 19,993 unique patients. This is the largest ...
Tomography, X-Ray Computed Radiography Machine Learning Lung Diseases Humans Neural Networks, Computer
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Dual-branch combination network (DCN): Towards accurate diagnosis and lesion segmentation of COVID-19 using CT images.

Medical image analysis Oct 8, 2020
The recent global outbreak and spread of coronavirus disease (COVID-19) makes it an imperative to develop accurate and efficient diagnostic tools for the disease as medical resources are getting increasingly constrained. Artificial intelligence (AI)-...
Neural Networks, Computer COVID-19 Humans Radiography, Thoracic Pneumonia, Viral SARS-CoV-2 Sensitivity and Specificity Tomography, X-Ray Computed
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PAIP 2019: Liver cancer segmentation challenge.

Medical image analysis Oct 8, 2020
Pathology Artificial Intelligence Platform (PAIP) is a free research platform in support of pathological artificial intelligence (AI). The main goal of the platform is to construct a high-quality pathology learning data set that will allow greater ac...
Image Processing, Computer-Assisted Tumor Burden Algorithms Humans Liver Neoplasms Artificial Intelligence
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Segmentation of cellular patterns in confocal images of melanocytic lesions in vivo via a multiscale encoder-decoder network (MED-Net).

Medical image analysis Oct 7, 2020
In-vivo optical microscopy is advancing into routine clinical practice for non-invasively guiding diagnosis and treatment of cancer and other diseases, and thus beginning to reduce the need for traditional biopsy. However, reading and analysis of the...
Microscopy, Confocal Humans Neural Networks, Computer Image Processing, Computer-Assisted
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ELNet:Automatic classification and segmentation for esophageal lesions using convolutional neural network.

Medical image analysis Oct 7, 2020
Automatic and accurate esophageal lesion classification and segmentation is of great significance to clinically estimate the lesion statuses of the esophageal diseases and make suitable diagnostic schemes. Due to individual variations and visual simi...
Humans Neural Networks, Computer
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Biomechanically constrained non-rigid MR-TRUS prostate registration using deep learning based 3D point cloud matching.

Medical image analysis Oct 7, 2020
A non-rigid MR-TRUS image registration framework is proposed for prostate interventions. The registration framework consists of a convolutional neural networks (CNN) for MR prostate segmentation, a CNN for TRUS prostate segmentation and a point-cloud...
Image Processing, Computer-Assisted Deep Learning Magnetic Resonance Imaging Ultrasonography Prostatic Neoplasms Humans Male
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Eigenrank by committee: Von-Neumann entropy based data subset selection and failure prediction for deep learning based medical image segmentation.

Medical image analysis Oct 7, 2020
Manual delineation of anatomy on existing images is the basis of developing deep learning algorithms for medical image segmentation. However, manual segmentation is tedious. It is also expensive because clinician effort is necessary to ensure correct...
Deep Learning Humans Entropy Algorithms
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