Vision-and-language(V&L) models take image and text as input and learn to capture the associations between them.
Alternative machine learning approaches that are computationally light with low latency and can work with only a small training dataset are needed for applications where the insatiable demand of deep learning methods for computing power and large training data cannot be met.
Optics Signal Processing
We apply this approach to both 2D and 3D CNN architectures with our top model achieving an ROC-AUC value of 0. 74, with a sensitivity of 0. 70 and a specificity of 0. 81 for classifying TSS < 4. 5 hours.
no code implementations • 28 Sep 2020 • Osama N. Hassan, Serhat Sahin, Vahid Mohammadzadeh, Xiaohe Yang, Navid Amini, Apoorva Mylavarapu, Jack Martinyan, Tae Hong, Golnoush Mahmoudinezhad, Daniel Rueckert, Kouros Nouri-Mahdavi, Fabien Scalzo
The patient's OCT scan is predicted from three or two prior measurements.
Here, we propose the baseline MRI model to alternatively learn the appearance of mp-MRI using radiology-confirmed negative MRI cases via weakly supervised learning.
In this work, we present a novel convolutional neural net- work based method for perfusion map generation in dynamic suscepti- bility contrast-enhanced perfusion imaging.