204 citations · 321 across the 28 of their papers we have counts for
5 papers · 1 filter
A Stronger Baseline For Automatic Pfirrmann Grading Of Lumbar Spine MRI Using Deep Learning
Narasimharao Kowlagi, Huy Hoang Nguyen, Terence McSweeney +4
This paper addresses the challenge of grading visual features in lumbar spine MRI using Deep Learning. Such a method is essential for the automatic quantification of structural cha…
Clinically-Inspired Multi-Agent Transformers for Disease Trajectory Forecasting from Multimodal Data
Huy Hoang Nguyen, Matthew B. Blaschko, Simo Saarakkala +1
Deep neural networks are often applied to medical images to automate the problem of medical diagnosis. However, a more clinically relevant question that practitioners usually face…
On confidence intervals for precision matrices and the eigendecomposition of covariance matrices
Teodora Popordanoska, Aleksei Tiulpin, Wacha Bounliphone +1
The eigendecomposition of a matrix is the central procedure in probabilistic models based on matrix factorization, for instance principal component analysis and topic models. Quant…
AdaTriplet: Adaptive Gradient Triplet Loss with Automatic Margin Learning for Forensic Medical Image Matching
Khanh Nguyen, Huy Hoang Nguyen, Aleksei Tiulpin
This paper tackles the challenge of forensic medical image matching (FMIM) using deep neural networks (DNNs). FMIM is a particular case of content-based image retrieval (CBIR). The…
Predicting Knee Osteoarthritis Progression from Structural MRI using Deep Learning
Egor Panfilov, Simo Saarakkala, Miika T. Nieminen +1
Accurate prediction of knee osteoarthritis (KOA) progression from structural MRI has a potential to enhance disease understanding and support clinical trials. Prior art focused on…