The Journal of the Acoustical Society of America
Jan 1, 2021
This paper is part of a special issue on machine learning in acoustics. A model-based convolutional neural network (CNN) approach is presented to test the viability of this method as an alternative to conventional matched-field processing (MFP) for u...
BACKGROUND: Interpretation of medical images for the diagnosis and treatment of complex diseases from high-dimensional and heterogeneous data remains a key challenge in transforming healthcare. In the last few years, both supervised and unsupervised ...
Journal of X-ray science and technology
Jan 1, 2021
The excessive radiation doses in the application of computed tomography (CT) technology pose a threat to the health of patients. However, applying a low radiation dose in CT can result in severe artifacts and noise in the captured images, thus affect...
BACKGROUND: Variations of image segmentation techniques, particularly those used for Brain MRI segmentation, vary in complexity from basic standard Fuzzy C-means (FCM) to more complex and enhanced FCM techniques.
Technology and health care : official journal of the European Society for Engineering and Medicine
Jan 1, 2021
BACKGROUND: Convolution neural network is often superior to other similar algorithms in image classification. Convolution layer and sub-sampling layer have the function of extracting sample features, and the feature of sharing weights greatly reduces...
Technology and health care : official journal of the European Society for Engineering and Medicine
Jan 1, 2021
BACKGROUND: Medical patients can be diagnosed early, however it is difficult to extract effective features in medical image segmentation based on semantic information.
BACKGROUND: Detailed pathology analysis and morphological quantification is tedious and prone to errors. Automatic image analysis can help to increase objectivity and reduce time. Here, we present the evaluation of the DeePathology STUDIO™ for automa...
BACKGROUND: The emergence of generative adversarial networks (GANs) has provided new technology and framework for the application of medical images. Specifically, a GAN requires little to no labeled data to obtain high-quality data that can be genera...
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