9 papers
Deep Psychovisual Image Representations
Wendi Ma, Aryaman Sharma, Wei Dai +1
Psychovisual models suggest human vision decouples low-level feature extraction from higher cognition by first forming intermediate abstractions. In contrast, deep learning-based v…
Von Neumann Networks
Shekhar S. Chandra
In the mid-twentieth century, mathematician and polymath John von Neumann created a computational system on an array of cells as a simple model of the human brain, where each cell…
Machine Learning Applications in Traumatic Brain Injury: A Spotlight on Mild TBI
Hanem Ellethy, Shekhar S. Chandra, Viktor Vegh
Traumatic Brain Injury (TBI) poses a significant global public health challenge, contributing to high morbidity and mortality rates and placing a substantial economic burden on hea…
Multi-scale MRI reconstruction via dilated ensemble networks
Wendi Ma, Marlon Bran Lorenzana, Wei Dai +2
As aliasing artefacts are highly structural and non-local, many MRI reconstruction networks use pooling to enlarge filter coverage and incorporate global context. However, this ina…
Enhancing mTBI Diagnosis with Residual Triplet Convolutional Neural Network Using 3D CT
Hanem Ellethy, Shekhar S. Chandra, Viktor Vegh
Mild Traumatic Brain Injury (mTBI) is a common and challenging condition to diagnose accurately. Timely and precise diagnosis is essential for effective treatment and improved pati…
Single Image Compressed Sensing MRI via a Self-Supervised Deep Denoising Approach
Marlon Bran Lorenzana, Feng Liu, Shekhar S. Chandra
Popular methods in compressed sensing (CS) are dependent on deep learning (DL), where large amounts of data are used to train non-linear reconstruction models. However, ensuring ge…