Aleksei Tiulpin | DeepAI

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∙ 07/03/2023

End-To-End Prediction of Knee Osteoarthritis Progression With Multi-Modal Transformers

Knee Osteoarthritis (KOA) is a highly prevalent chronic musculoskeletal ...

0 Egor Panfilov, et al. ∙

∙ 10/26/2022

A Stronger Baseline For Automatic Pfirrmann Grading Of Lumbar Spine MRI Using Deep Learning

This paper addresses the challenge of grading visual features in lumbar ...

0 Narasimharao Kowlagi, et al. ∙

∙ 10/25/2022

Clinically-Inspired Multi-Agent Transformers for Disease Trajectory Forecasting from Multimodal Data

Deep neural networks are often applied to medical images to automate the...

0 Huy Hoang Nguyen, et al. ∙

∙ 08/25/2022

On confidence intervals for precision matrices and the eigendecomposition of covariance matrices

The eigendecomposition of a matrix is the central procedure in probabili...

14 Teodora Popordanoska, et al. ∙

∙ 05/05/2022

AdaTriplet: Adaptive Gradient Triplet Loss with Automatic Margin Learning for Forensic Medical Image Matching

This paper tackles the challenge of forensic medical image matching (FMI...

0 Khanh Nguyen, et al. ∙

∙ 01/26/2022

Predicting Knee Osteoarthritis Progression from Structural MRI using Deep Learning

Accurate prediction of knee osteoarthritis (KOA) progression from struct...

0 Egor Panfilov, et al. ∙

∙ 06/08/2021

Targeted Active Learning for Bayesian Decision-Making

Active learning is usually applied to acquire labels of informative data...

0 Louis Filstroff, et al. ∙

∙ 05/29/2021

Greedy Bayesian Posterior Approximation with Deep Ensembles

Ensembles of independently trained neural networks are a state-of-the-ar...

0 Aleksei Tiulpin, et al. ∙

∙ 04/08/2021

DeepProg: A Transformer-based Framework for Predicting Disease Prognosis

A vast majority of deep learning methods are built to automate diagnosti...

0 Huy Hoang Nguyen, et al. ∙

∙ 12/04/2020

Deep Learning for Wrist Fracture Detection: Are We There Yet?

Wrist Fracture is the most common type of fracture with a high incidence...

13 Abu Mohammed Raisuddin, et al. ∙

∙ 03/04/2020

Semixup: In- and Out-of-Manifold Regularization for Deep Semi-Supervised Knee Osteoarthritis Severity Grading from Plain Radiographs

Knee osteoarthritis (OA) is one of the highest disability factors in the...

1 Huy Hoang Nguyen, et al. ∙

∙ 08/21/2019

Adaptive Segmentation of Knee Radiographs for Selecting the Optimal ROI in Texture Analysis

The purposes of this study were to investigate: 1) the effect of placeme...

1 Neslihan Bayramoglu, et al. ∙

∙ 08/12/2019

Improving Robustness of Deep Learning Based Knee MRI Segmentation: Mixup and Adversarial Domain Adaptation

Degeneration of articular cartilage (AC) is actively studied in knee ost...

5 Egor Panfilov, et al. ∙

∙ 08/08/2019

Bayesian Feature Pyramid Networks for Automatic Multi-Label Segmentation of Chest X-rays and Assessment of Cardio-Thoratic Ratio

Cardiothoratic ratio (CTR) estimated from chest radiographs is a marker ...

8 Roman Solovyev, et al. ∙

∙ 07/29/2019

KNEEL: Knee Anatomical Landmark Localization Using Hourglass Networks

This paper addresses the challenge of localization of anatomical landmar...

2 Aleksei Tiulpin, et al. ∙

∙ 07/18/2019

Automatic Grading of Individual Knee Osteoarthritis Features in Plain Radiographs using Deep Convolutional Neural Networks

Knee osteoarthritis (OA) is the most common musculoskeletal disease in t...

1 Aleksei Tiulpin, et al. ∙

∙ 07/11/2019

Deep-Learning for Tidemark Segmentation in Human Osteochondral Tissues Imaged with Micro-computed Tomography

Three-dimensional (3D) semi-quantitative grading of pathological feature...

4 Aleksei Tiulpin, et al. ∙

∙ 05/05/2019

Breast Tumor Cellularity Assessment using Deep Neural Networks

Breast cancer is one of the main causes of death worldwide. Histopatholo...

7 Alexander Rakhlin, et al. ∙

∙ 04/12/2019

Multimodal Machine Learning-based Knee Osteoarthritis Progression Prediction from Plain Radiographs and Clinical Data

Knee osteoarthritis (OA) is the most common musculoskeletal disease with...

8 Aleksei Tiulpin, et al. ∙

∙ 10/19/2018

DGC-Net: Dense Geometric Correspondence Network

This paper addresses the challenge of dense pixel correspondence estimat...

4 Iaroslav Melekhov, et al. ∙

∙ 10/29/2017

Automatic Knee Osteoarthritis Diagnosis from Plain Radiographs: A Deep Learning-Based Approach

Knee osteoarthritis (OA) is the most common musculoskeletal disorder. OA...

0 Aleksei Tiulpin, et al. ∙

∙ 01/31/2017

A novel method for automatic localization of joint area on knee plain radiographs

Osteoarthritis (OA) is a common musculoskeletal condition typically diag...

0 Aleksei Tiulpin, et al. ∙

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