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Use of a convolutional neural network and quantitative ultrasound for diagnosis of fatty liver
(2020-10-30)
Quantitative ultrasound (QUS) was used to classify rabbits that were induced to have liver disease by placing them on a fatty diet for a defined duration and/or periodically injecting them with CCl4. The ground truth of ...
Multimodal unrolled robust PCA for background-foreground separation
(2022)
Background foreground separation (BFS) is a critical computer vision task aimed at distinguishing dynamic foreground objects from static backgrounds. While consumer cameras are widely used due to their affordability, high ...
Multimodal fusion using sparse CCA for breast cancer survival prediction
(2021-04-13)
Effective understanding of diseases like cancer necessitates integrating diverse information across various physical scales through multimodal data. In this study, we introduce a novel feature embedding module based on ...
Use of a convolutional neural network and quantitative ultrasound for diagnosis of fatty liver
(2022-03-01)
Quantitative ultrasound (QUS) was used to classify rabbits that were induced to have liver disease by placing them on a fatty diet for a defined duration and/or periodically injecting them with CCl4. The ground truth of ...
Towards a Comprehensive Solution for a Vision-Based Digitized Neurological Examination
(2022-08-08)
The ability to use digitally recorded and quantified neurological exam information is important to help healthcare systems deliver better care, in-person and via telehealth, as they compensate for a growing shortage of ...
Efficient human vision inspired action recognition using adaptive spatiotemporal sampling
(2022-07-14)
Adaptive sampling that exploits the spatiotemporal redundancy in videos is critical for always-on action recognition on wearable devices with limited computing and battery resources. The commonly used fixed sampling strategy ...
Towards a comprehensive solution for a vision-based digitized neurological examination
(2022-08)
The ability to use digitally recorded and quantified neurological exam information is important to help healthcare systems deliver better care, in-person and via telehealth, as they compensate for a growing shortage of ...