AIMC Topic:
Image Interpretation, Computer-Assisted

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Machine learning will transform radiology significantly within the next 5 years.

Medical physics Apr 20, 2017
Radiology Image Interpretation, Computer-Assisted Pattern Recognition, Automated Machine Learning Radiography Humans
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Improving automated multiple sclerosis lesion segmentation with a cascaded 3D convolutional neural network approach.

NeuroImage Apr 19, 2017
In this paper, we present a novel automated method for White Matter (WM) lesion segmentation of Multiple Sclerosis (MS) patient images. Our approach is based on a cascade of two 3D patch-wise convolutional neural networks (CNN). The first network is ...
Humans Neural Networks, Computer Brain Image Interpretation, Computer-Assisted Neuroimaging White Matter Imaging, Three-Dimensional Multiple Sclerosis
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Two-phase deep convolutional neural network for reducing class skewness in histopathological images based breast cancer detection.

Computers in biology and medicine Apr 18, 2017
Different types of breast cancer are affecting lives of women across the world. Common types include Ductal carcinoma in situ (DCIS), Invasive ductal carcinoma (IDC), Tubular carcinoma, Medullary carcinoma, and Invasive lobular carcinoma (ILC). While...
Histocytochemistry Mitosis Image Interpretation, Computer-Assisted Cell Nucleus Machine Learning Algorithms Breast Neoplasms ROC Curve Humans Female Neural Networks, Computer
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Convolutional neural network regression for short-axis left ventricle segmentation in cardiac cine MR sequences.

Medical image analysis Apr 12, 2017
Automated left ventricular (LV) segmentation is crucial for efficient quantification of cardiac function and morphology to aid subsequent management of cardiac pathologies. In this paper, we parameterize the complete (all short axis slices and phases...
Image Interpretation, Computer-Assisted Magnetic Resonance Imaging, Cine Neural Networks, Computer Machine Learning Regression Analysis Heart Ventricles Reproducibility of Results Humans
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Gaze-contingent perceptually enabled interactions in the operating theatre.

International journal of computer assisted radiology and surgery Apr 10, 2017
PURPOSE: Improved surgical outcome and patient safety in the operating theatre are constant challenges. We hypothesise that a framework that collects and utilises information -especially perceptually enabled ones-from multiple sources, could help to ...
Operating Rooms Fixation, Ocular Robotics Eye Movement Measurements Minimally Invasive Surgical Procedures Humans Workflow Image Interpretation, Computer-Assisted
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Quantitative analysis of patients with celiac disease by video capsule endoscopy: A deep learning method.

Computers in biology and medicine Apr 8, 2017
BACKGROUND: Celiac disease is one of the most common diseases in the world. Capsule endoscopy is an alternative way to visualize the entire small intestine without invasiveness to the patient. It is useful to characterize celiac disease, but hours ar...
Capsule Endoscopy Celiac Disease Machine Learning Algorithms Image Interpretation, Computer-Assisted Humans Neural Networks, Computer
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A Novel Fusion Framework Based on Adaptive PCNN in NSCT Domain for Whole-Body PET and CT Images.

Computational and mathematical methods in medicine Apr 3, 2017
The PET and CT fusion images, combining the anatomical and functional information, have important clinical meaning. This paper proposes a novel fusion framework based on adaptive pulse-coupled neural networks (PCNNs) in nonsubsampled contourlet trans...
Image Interpretation, Computer-Assisted Humans Tomography, X-Ray Computed Algorithms Positron-Emission Tomography Neural Networks, Computer
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Automated Identification of Diabetic Retinopathy Using Deep Learning.

Ophthalmology Mar 27, 2017
PURPOSE: Diabetic retinopathy (DR) is one of the leading causes of preventable blindness globally. Performing retinal screening examinations on all diabetic patients is an unmet need, and there are many undiagnosed and untreated cases of DR. The obje...
Ophthalmologists ROC Curve Image Interpretation, Computer-Assisted Diagnostic Techniques, Ophthalmological Algorithms Reproducibility of Results Diabetic Retinopathy Humans Neural Networks, Computer Machine Learning
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A multi-resolution approach for spinal metastasis detection using deep Siamese neural networks.

Computers in biology and medicine Mar 27, 2017
Spinal metastasis, a metastatic cancer of the spine, is the most common malignant disease in the spine. In this study, we investigate the feasibility of automated spinal metastasis detection in magnetic resonance imaging (MRI) by using deep learning ...
ROC Curve Magnetic Resonance Imaging Humans Image Interpretation, Computer-Assisted Spinal Neoplasms Neural Networks, Computer Female Male Aged Middle Aged
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Multiscale Rotation-Invariant Convolutional Neural Networks for Lung Texture Classification.

IEEE journal of biomedical and health informatics Mar 21, 2017
We propose a new multiscale rotation-invariant convolutional neural network (MRCNN) model for classifying various lung tissue types on high-resolution computed tomography. MRCNN employs Gabor-local binary pattern that introduces a good property in im...
Humans Algorithms Lung Neural Networks, Computer Pattern Recognition, Automated Lung Diseases, Interstitial Image Interpretation, Computer-Assisted
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