AIMC Topic: Diagnostic Imaging

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Current applications and future directions of deep learning in musculoskeletal radiology.

Skeletal radiology Aug 4, 2019
Deep learning with convolutional neural networks (CNN) is a rapidly advancing subset of artificial intelligence that is ideally suited to solving image-based problems. There are an increasing number of musculoskeletal applications of deep learning, w...
Musculoskeletal System Radiology Image Interpretation, Computer-Assisted Musculoskeletal Diseases Humans Neural Networks, Computer Deep Learning Diagnostic Imaging
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Advances in computer-aided medical systems and clinical measurement.

Computer assisted surgery (Abingdon, England) Aug 2, 2019
Humans Artificial Intelligence Surgery, Computer-Assisted Image Interpretation, Computer-Assisted Phantoms, Imaging Computer-Aided Design Diagnostic Imaging Electroencephalography
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Reducing the Hausdorff Distance in Medical Image Segmentation With Convolutional Neural Networks.

IEEE transactions on medical imaging Jul 19, 2019
The Hausdorff Distance (HD) is widely used in evaluating medical image segmentation methods. However, the existing segmentation methods do not attempt to reduce HD directly. In this paper, we present novel loss functions for training convolutional ne...
Diagnostic Imaging Prostate Humans Neural Networks, Computer Algorithms Male Image Processing, Computer-Assisted Liver
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Machine Learning With Deep Neural Nets Artificially Augmenting My Intelligence in a Narrow but Occasionally Superhuman Kind of Way.

Journal of the American College of Radiology : JACR Jul 19, 2019
Machine Learning Forecasting Diagnostic Imaging Neural Networks, Computer Artificial Intelligence Humans
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Engineering approaches for characterizing soft tissue mechanical properties: A review.

Clinical biomechanics (Bristol, Avon) Jul 16, 2019
From cancer diagnosis to detailed characterization of arterial wall biomechanics, the elastic property of tissues is widely studied as an early sign of disease onset. The fibrous structural features of tissues are a direct measure of its health and f...
Fiber Optic Technology Liver Area Under Curve Diagnostic Imaging Tomography, Optical Coherence Equipment Design Biomechanical Phenomena Humans Male Neoplasms Machine Learning Female Breast Bioengineering Cell Membrane Brain Neoplasms Robotic Surgical Procedures Microscopy, Atomic Force Elasticity Imaging Techniques Vagina Elasticity Stomach Prostate
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Flexible Prediction of CT Images From MRI Data Through Improved Neighborhood Anchored Regression for PET Attenuation Correction.

IEEE journal of biomedical and health informatics Jul 9, 2019
Given the complicated relationship between the magnetic resonance imaging (MRI) signals and the attenuation values, the attenuation correction in hybrid positron emission tomography (PET)/MRI systems remains a challenging task. Currently, existing me...
Brain Female Aged Humans Regression Analysis Diagnostic Imaging Middle Aged Deep Learning Image Processing, Computer-Assisted Adult Male
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Creating the Black Box: A Primer on Convolutional Neural Network Use in Image Interpretation.

Current problems in diagnostic radiology Jul 9, 2019
Convolutional neural networks have been shown to demonstrate high diagnostic performance in radiologic image interpretation tasks ranging from recognition of acute stroke on computed tomography to identification of tuberculosis on plain radiographs. ...
Humans Neural Networks, Computer Machine Learning Diagnostic Imaging Image Interpretation, Computer-Assisted
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Imaging Quality Control in the Era of Artificial Intelligence.

Journal of the American College of Radiology : JACR Jun 26, 2019
The advent of artificial intelligence (AI) promises to have a transformational impact on quality in medicine, including in radiology. However, experience has shown that quality tools alone are often not sufficient to bring about consistent excellent ...
Diagnostic Imaging Radiology Positron-Emission Tomography Quality Control Automation Radiation Exposure Humans Artificial Intelligence Forecasting Tomography, X-Ray Computed Risk Assessment
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Overview of image-to-image translation by use of deep neural networks: denoising, super-resolution, modality conversion, and reconstruction in medical imaging.

Radiological physics and technology Jun 20, 2019
Since the advent of deep convolutional neural networks (DNNs), computer vision has seen an extremely rapid progress that has led to huge advances in medical imaging. Every year, many new methods are reported at conferences such as the International C...
Signal-To-Noise Ratio Deep Learning Image Processing, Computer-Assisted Diagnostic Imaging
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Convolutional sparse kernel network for unsupervised medical image analysis.

Medical image analysis Jun 12, 2019
The availability of large-scale annotated image datasets and recent advances in supervised deep learning methods enable the end-to-end derivation of representative image features that can impact a variety of image analysis problems. Such supervised a...
Unsupervised Machine Learning Diagnostic Imaging Supervised Machine Learning Humans Image Processing, Computer-Assisted
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