62 citations · 99 across the 6 of their papers we have counts for
8 papers
XVertNet: Unsupervised Contrast Enhancement of Vertebral Structures with Dynamic Self-Tuning Guidance and Multi-Stage Analysis
Ella Eidlin, Assaf Hoogi, Hila Rozen +2
Chest X-rays remain the primary diagnostic tool in emergency medicine, yet their limited ability to capture fine anatomical details can result in missed or delayed diagnoses. To ad…
Break a Lag: Triple Exponential Moving Average for Enhanced Optimization
Roi Peleg, Yair Smadar, Teddy Lazebnik +1
The performance of deep learning models is critically dependent on sophisticated optimization strategies. While existing optimizers have shown promising results, many rely on first…
Deep Active Lesion Segmentation
Ali Hatamizadeh, Assaf Hoogi, Debleena Sengupta +4
Lesion segmentation is an important problem in computer-assisted diagnosis that remains challenging due to the prevalence of low contrast, irregular boundaries that are unamenable…
From voxels to pixels and back: Self-supervision in natural-image reconstruction from fMRI
Roman Beliy, Guy Gaziv, Assaf Hoogi +3
Reconstructing observed images from fMRI brain recordings is challenging. Unfortunately, acquiring sufficient "labeled" pairs of {Image, fMRI} (i.e., images with their correspondin…
Self-Attention Capsule Networks for Object Classification
Assaf Hoogi, Brian Wilcox, Yachee Gupta +1
We propose a novel architecture for object classification, called Self-Attention Capsule Networks (SACN). SACN is the first model that incorporates the Self-Attention mechanism as…
TVAE: Triplet-Based Variational Autoencoder using Metric Learning
Haque Ishfaq, Assaf Hoogi, Daniel Rubin
Deep metric learning has been demonstrated to be highly effective in learning semantic representation and encoding information that can be used to measure data similarity, by relyi…