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Image processing pipeline for liver fibrosis classification using ultrasound shear wave elastography
Summary
Summary
The purpose of this study was to develop an automated method for classifying liver fibrosis stage >=F2 based on ultrasound shear wave elastography (SWE) and to assess the system's performance in comparison with a reference manual approach. The reference approach consists of manually selecting a region of interest from each...
This looks like that: deep learning for interpretable image recognition
Summary
Summary
When we are faced with challenging image classification tasks, we often explain our reasoning by dissecting the image, and pointing out prototypical aspects of one class or another. The mounting evidence for each of the classes helps us make our final decision. In this work, we introduce a deep network...
Feature forwarding for efficient single image dehazing
Summary
Summary
Haze degrades content and obscures information of images, which can negatively impact vision-based decision-making in real-time systems. In this paper, we propose an efficient fully convolutional neural network (CNN) image dehazing method designed to run on edge graphical processing units (GPUs). We utilize three variants of our architecture to explore...
Machine learning for medical ultrasound: status, methods, and future opportunities
Summary
Summary
Ultrasound (US) imaging is the most commonly performed cross-sectional diagnostic imaging modality in the practice of medicine. It is low-cost, non-ionizing, portable, and capable of real-time image acquisition and display. US is a rapidly evolving technology with significant challenges and opportunities. Challenges include high inter- and intra-operator variability and limited...
Multi-modal audio, video and physiological sensor learning for continuous emotion prediction
Summary
Summary
The automatic determination of emotional state from multimedia content is an inherently challenging problem with a broad range of applications including biomedical diagnostics, multimedia retrieval, and human computer interfaces. The Audio Video Emotion Challenge (AVEC) 2016 provides a well-defined framework for developing and rigorously evaluating innovative approaches for estimating the...
Detecting depression using vocal, facial and semantic communication cues
Summary
Summary
Major depressive disorder (MDD) is known to result in neurophysiological and neurocognitive changes that affect control of motor, linguistic, and cognitive functions. MDD's impact on these processes is reflected in an individual's communication via coupled mechanisms: vocal articulation, facial gesturing and choice of content to convey in a dialogue. In...
How deep neural networks can improve emotion recognition on video data
Summary
Summary
We consider the task of dimensional emotion recognition on video data using deep learning. While several previous methods have shown the benefits of training temporal neural network models such as recurrent neural networks (RNNs) on hand-crafted features, few works have considered combining convolutional neural networks (CNNs) with RNNs. In this...
The Offshore Precipitation Capability
Summary
Summary
In this work, machine learning and image processing methods are used to estimate radar-like precipitation intensity and echo top heights beyond the range of weather radar. The technology, called the Offshore Precipitation Capability (OPC), combines global lightning data with existing radar mosaics, five Geostationary Operational Environmental Satellite (GOES) channels, and...
Time delay integration and in-pixel spatiotemporal filtering using a nanoscale digital CMOS focal plane readout
Summary
Summary
A digital focal plane array (DFPA) architecture has been developed that incorporates per-pixel full-dynamic-range analog-to-digital conversion and orthogonal-transfer-based realtime digital signal processing capability. Several long-wave infrared-optimized pixel processing focal plane readout integrated circuit (ROIC) designs have been implemented, each accommodating a 256 x 256 30-um-pitch detector array. Demonstrated in this...
A method for correcting Fourier transform spectrometer (FTS) dynamic alignment errors
Summary
Summary
The Cross-track Infrared Sounder (CrIS), like most Fourier Transform spectrometers, can be sensitive to mechanical disturbances during the time spectral data is collected. The Michelson interferometer within the spectrometer modulates input radiation at a frequency equal to the product of the wavenumber of the radiation and the constant optical path...