Aleksei Tiulpin

According to our database, Aleksei Tiulpin authored at least 28 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

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

Huy Hoang Nguyen, Matthew B. Blaschko, Simo Saarakkala, Aleksei Tiulpin

IEEE Trans. Medical Imaging, January, 2024

Beyond Classification: Definition and Density-based Estimation of Calibration in Object Detection.

Teodora Popordanoska, Aleksei Tiulpin, Matthew B. Blaschko

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

2023

Consistent and Asymptotically Unbiased Estimation of Proper Calibration Errors.

Teodora Popordanoska, Sebastian G. Gruber, Aleksei Tiulpin, Florian Büttner, Matthew B. Blaschko

CoRR, 2023

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

Egor Panfilov, Simo Saarakkala, Miika T. Nieminen, Aleksei Tiulpin

CoRR, 2023

Understanding metric-related pitfalls in image analysis validation.

Annika Reinke, Minu Tizabi, Michael Baumgartner, Matthias Eisenmann, Doreen Heckmann-Nötzel, A. Emre Kavur, Tim Rädsch, Carole H. Sudre, Laura Ación, Michela Antonelli, Tal Arbel, Spyridon Bakas, Arriel Benis, Matthew B. Blaschko, Florian Büttner, M. Jorge Cardoso, Veronika Cheplygina, Jianxu Chen, Evangelia Christodoulou, Beth A. Cimini, Gary S. Collins, Keyvan Farahani, Luciana Ferrer, Adrian Galdran, Bram van Ginneken, Ben Glocker, Patrick Godau, Robert Haase, Daniel A. Hashimoto, Michael M. Hoffman, Merel Huisman, Fabian Isensee, Pierre Jannin, Charles E. Kahn, Dagmar Kainmueller, Bernhard Kainz, Alexandros Karargyris, Alan Karthikesalingam, Hannes Kenngott, Jens Kleesiek, Florian Kofler, Thijs Kooi, Annette Kopp-Schneider, Michal Kozubek, Anna Kreshuk, Tahsin M. Kurç, Bennett A. Landman, Geert Litjens, Amin Madani, Klaus H. Maier-Hein, Anne L. Martel, Peter Mattson, Erik Meijering, Bjoern H. Menze, Karel G. M. Moons, Henning Müller, Brennan Nichyporuk, Felix Nickel, Jens Petersen, Susanne M. Rafelski, Nasir M. Rajpoot, Mauricio Reyes, Michael A. Riegler, Nicola Rieke, Julio Saez-Rodriguez, Clara I. Sánchez, Shravya Shetty, Maarten van Smeden, Ronald M. Summers, Abdel A. Taha, Aleksei Tiulpin, Sotirios A. Tsaftaris, Ben Van Calster, Gaël Varoquaux, Manuel Wiesenfarth, Ziv R. Yaniv, Paul F. Jäger, Lena Maier-Hein

CoRR, 2023

MRI2Mesh: Intervertebral Disc Mesh Generation from Low Resolution MRI Using Graph Neural Networks with Cross Level Feature Fusion.

Sai Natarajan, Aleksei Tiulpin, Ludovic Humbert, Miguel Ángel González Ballester

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.

Narasimharao Kowlagi, Huy Hoang Nguyen, Terence McSweeney, Simo Saarakkala, Juhani Määttä, Jaro Karppinen, Aleksei Tiulpin

Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023

2022

Greedy Bayesian Posterior Approximation with Deep Ensembles.

Aleksei Tiulpin, Matthew B. Blaschko

Trans. Mach. Learn. Res., 2022

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

Teodora Popordanoska, Aleksei Tiulpin, Wacha Bounliphone, Matthew B. Blaschko

CoRR, 2022

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

Khanh Nguyen, Huy Hoang Nguyen, Aleksei Tiulpin

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022

Deep Semi-Supervised Active Learning for Knee Osteoarthritis Severity Grading.

Abu Mohammed Raisuddin, Huy Hoang Nguyen, Aleksei Tiulpin

Proceedings of the 19th IEEE International Symposium on Biomedical Imaging, 2022

Predicting Knee Osteoarthritis Progression from Structural MRI Using Deep Learning.

Egor Panfilov, Simo Saarakkala, Miika T. Nieminen, Aleksei Tiulpin

Proceedings of the 19th IEEE International Symposium on Biomedical Imaging, 2022

CLIMAT: Clinically-Inspired Multi-Agent Transformers for Knee Osteoarthritis Trajectory Forecasting.

Huy Hoang Nguyen, Simo Saarakkala, Matthew B. Blaschko, Aleksei Tiulpin

Proceedings of the 19th IEEE International Symposium on Biomedical Imaging, 2022

2021

Targeted Active Learning for Bayesian Decision-Making.

Louis Filstroff, Iiris Sundin, Petrus Mikkola, Aleksei Tiulpin, Juuso Kylmäoja, Samuel Kaski

CoRR, 2021

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

Huy Hoang Nguyen, Simo Saarakkala, Matthew B. Blaschko, Aleksei Tiulpin

CoRR, 2021

2020

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

Huy Hoang Nguyen, Simo Saarakkala, Matthew B. Blaschko, Aleksei Tiulpin

IEEE Trans. Medical Imaging, 2020

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

Abu Mohammed Raisuddin, Elias Vaattovaara, Mika Nevalainen, Marko Nikki, Elina Järvenpää, Kaisa Makkonen, Pekka Pinola, Tuula Palsio, Arttu Niemensivu, Osmo Tervonen, Aleksei Tiulpin

CoRR, 2020

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

Aleksei Tiulpin, Mikko Finnilä, Petri Lehenkari, Heikki J. Nieminen, Simo Saarakkala

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.

Roman A. Solovyev, Iaroslav Melekhov, Timo Lesonen, Elias Vaattovaara, Osmo Tervonen, Aleksei Tiulpin

Proceedings of the Advanced Concepts for Intelligent Vision Systems, 2020

2019

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

Neslihan Bayramoglu, Aleksei Tiulpin, Jukka Hirvasniemi, Miika T. Nieminen, Simo Saarakkala

CoRR, 2019

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

Aleksei Tiulpin, Simo Saarakkala

CoRR, 2019

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

Aleksei Tiulpin, Stefan Klein, Sita M. A. Bierma-Zeinstra, Jérôme Thevenot, Esa Rahtu, Joyce van Meurs, Edwin H. G. Oei, Simo Saarakkala

CoRR, 2019

DGC-Net: Dense Geometric Correspondence Network.

Iaroslav Melekhov, Aleksei Tiulpin, Torsten Sattler, Marc Pollefeys, Esa Rahtu, Juho Kannala

Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2019

KNEEL: Knee Anatomical Landmark Localization Using Hourglass Networks.

Aleksei Tiulpin, Iaroslav Melekhov, Simo Saarakkala

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision Workshops, 2019

Breast Tumor Cellularity Assessment Using Deep Neural Networks.

Alexander Rakhlin, Aleksei Tiulpin, Alexey A. Shvets, Alexandr A. Kalinin, Vladimir I. Iglovikov, Sergey I. Nikolenko

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.

Egor Panfilov, Aleksei Tiulpin, Stefan Klein, Miika T. Nieminen, Simo Saarakkala

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.

Aleksei Tiulpin, Jérôme Thevenot, Esa Rahtu, Petri Lehenkari, Simo Saarakkala

CoRR, 2017

A Novel Method for Automatic Localization of Joint Area on Knee Plain Radiographs.

Aleksei Tiulpin, Jérôme Thevenot, Esa Rahtu, Simo Saarakkala

Proceedings of the Image Analysis - 20th Scandinavian Conference, 2017