Aleksei Tiulpin

Orcid: 0000-0002-7852-4141

Affiliations:
  • University of Oulu, Finland


According to our database1, Aleksei Tiulpin authored at least 33 papers between 2017 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Online presence:

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Bibliography

2024
Clinically-Inspired Multi-Agent Transformers for Disease Trajectory Forecasting From Multimodal Data.
IEEE Trans. Medical Imaging, January, 2024

Targeted Active Learning for Bayesian Decision-Making.
Trans. Mach. Learn. Res., 2024

LoG-VMamba: Local-Global Vision Mamba for Medical Image Segmentation.
CoRR, 2024

Active Sensing of Knee Osteoarthritis Progression with Reinforcement Learning.
CoRR, 2024

Image-level Regression for Uncertainty-aware Retinal Image Segmentation.
CoRR, 2024

Beyond Classification: Definition and Density-based Estimation of Calibration in Object Detection.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

A Scanning Laser Ophthalmoscopy Image Database and Trustworthy Retinal Disease Detection Method.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024

SiNGR: Brain Tumor Segmentation via Signed Normalized Geodesic Transform Regression.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024

Consistent and Asymptotically Unbiased Estimation of Proper Calibration Errors.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023
End-To-End Prediction of Knee Osteoarthritis Progression With Multi-Modal Transformers.
CoRR, 2023

Understanding metric-related pitfalls in image analysis validation.
CoRR, 2023

MRI2Mesh: Intervertebral Disc Mesh Generation from Low Resolution MRI Using Graph Neural Networks with Cross Level Feature Fusion.
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023

A Stronger Baseline For Automatic Pfirrmann Grading Of Lumbar Spine Mri Using Deep Learning.
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023

2022
Greedy Bayesian Posterior Approximation with Deep Ensembles.
Trans. Mach. Learn. Res., 2022

On confidence intervals for precision matrices and the eigendecomposition of covariance matrices.
CoRR, 2022

AdaTriplet: Adaptive Gradient Triplet Loss with Automatic Margin Learning for Forensic Medical Image Matching.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022

Deep Semi-Supervised Active Learning for Knee Osteoarthritis Severity Grading.
Proceedings of the 19th IEEE International Symposium on Biomedical Imaging, 2022

Predicting Knee Osteoarthritis Progression from Structural MRI Using Deep Learning.
Proceedings of the 19th IEEE International Symposium on Biomedical Imaging, 2022

CLIMAT: Clinically-Inspired Multi-Agent Transformers for Knee Osteoarthritis Trajectory Forecasting.
Proceedings of the 19th IEEE International Symposium on Biomedical Imaging, 2022

2021
DeepProg: A Transformer-based Framework for Predicting Disease Prognosis.
CoRR, 2021

2020
Semixup: In- and Out-of-Manifold Regularization for Deep Semi-Supervised Knee Osteoarthritis Severity Grading From Plain Radiographs.
IEEE Trans. Medical Imaging, 2020

Deep Learning for Wrist Fracture Detection: Are We There Yet?
CoRR, 2020

Deep-Learning for Tidemark Segmentation in Human Osteochondral Tissues Imaged with Micro-computed Tomography.
Proceedings of the Advanced Concepts for Intelligent Vision Systems, 2020

Bayesian Feature Pyramid Networks for Automatic Multi-label Segmentation of Chest X-rays and Assessment of Cardio-Thoratic Ratio.
Proceedings of the Advanced Concepts for Intelligent Vision Systems, 2020

2019
Adaptive Segmentation of Knee Radiographs for Selecting the Optimal ROI in Texture Analysis.
CoRR, 2019

Automatic Grading of Individual Knee Osteoarthritis Features in Plain Radiographs using Deep Convolutional Neural Networks.
CoRR, 2019

Multimodal Machine Learning-based Knee Osteoarthritis Progression Prediction from Plain Radiographs and Clinical Data.
CoRR, 2019

DGC-Net: Dense Geometric Correspondence Network.
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2019

KNEEL: Knee Anatomical Landmark Localization Using Hourglass Networks.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision Workshops, 2019

Breast Tumor Cellularity Assessment Using Deep Neural Networks.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision Workshops, 2019

Improving Robustness of Deep Learning Based Knee MRI Segmentation: Mixup and Adversarial Domain Adaptation.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision Workshops, 2019

2017
Automatic Knee Osteoarthritis Diagnosis from Plain Radiographs: A Deep Learning-Based Approach.
CoRR, 2017

A Novel Method for Automatic Localization of Joint Area on Knee Plain Radiographs.
Proceedings of the Image Analysis - 20th Scandinavian Conference, 2017


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