no code implementations • 14 Dec 2023 • Teodora Popordanoska, Sebastian G. Gruber, Aleksei Tiulpin, Florian Buettner, Matthew B. Blaschko
Proper scoring rules evaluate the quality of probabilistic predictions, playing an essential role in the pursuit of accurate and well-calibrated models.
1 code implementation • 11 Dec 2023 • Teodora Popordanoska, Aleksei Tiulpin, Matthew B. Blaschko
Despite their impressive predictive performance in various computer vision tasks, deep neural networks (DNNs) tend to make overly confident predictions, which hinders their widespread use in safety-critical applications.
no code implementations • 3 Jul 2023 • Egor Panfilov, Simo Saarakkala, Miika T. Nieminen, Aleksei Tiulpin
In this study, we leveraged recent advances in Deep Learning and, using a Transformer approach, developed a unified framework for the multi-modal fusion of knee imaging data.
no code implementations • 3 Feb 2023 • Annika Reinke, Minu D. Tizabi, Michael Baumgartner, Matthias Eisenmann, Doreen Heckmann-Nötzel, A. Emre Kavur, Tim Rädsch, Carole H. Sudre, Laura Acion, Michela Antonelli, Tal Arbel, Spyridon Bakas, Arriel Benis, Matthew Blaschko, Florian Buettner, 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 Kurc, Bennett A. Landman, Geert Litjens, Amin Madani, Klaus Maier-Hein, Anne L. Martel, Peter Mattson, Erik Meijering, Bjoern Menze, Karel G. M. Moons, Henning Müller, Brennan Nichyporuk, Felix Nickel, Jens Petersen, Susanne M. Rafelski, Nasir 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
Validation metrics are key for the reliable tracking of scientific progress and for bridging the current chasm between artificial intelligence (AI) research and its translation into practice.
no code implementations • 26 Oct 2022 • Narasimharao Kowlagi, Huy Hoang Nguyen, Terence McSweeney, Simo Saarakkala, Juhani määttä, Jaro Karppinen, Aleksei Tiulpin
This paper addresses the challenge of grading visual features in lumbar spine MRI using Deep Learning.
1 code implementation • 25 Oct 2022 • Huy Hoang Nguyen, Matthew B. Blaschko, Simo Saarakkala, Aleksei Tiulpin
Deep neural networks are often applied to medical images to automate the problem of medical diagnosis.
no code implementations • 25 Aug 2022 • Teodora Popordanoska, Aleksei Tiulpin, Wacha Bounliphone, Matthew B. Blaschko
Moreover, we derive a method to bound the entries of the inverse covariance matrix, the so-called precision matrix.
1 code implementation • 3 Jun 2022 • Lena Maier-Hein, Annika Reinke, Patrick Godau, Minu D. Tizabi, Florian Buettner, Evangelia Christodoulou, Ben Glocker, Fabian Isensee, Jens Kleesiek, Michal Kozubek, Mauricio Reyes, Michael A. Riegler, Manuel Wiesenfarth, A. Emre Kavur, Carole H. Sudre, Michael Baumgartner, Matthias Eisenmann, Doreen Heckmann-Nötzel, Tim Rädsch, Laura Acion, Michela Antonelli, Tal Arbel, Spyridon Bakas, Arriel Benis, Matthew Blaschko, M. Jorge Cardoso, Veronika Cheplygina, Beth A. Cimini, Gary S. Collins, Keyvan Farahani, Luciana Ferrer, Adrian Galdran, Bram van Ginneken, Robert Haase, Daniel A. Hashimoto, Michael M. Hoffman, Merel Huisman, Pierre Jannin, Charles E. Kahn, Dagmar Kainmueller, Bernhard Kainz, Alexandros Karargyris, Alan Karthikesalingam, Hannes Kenngott, Florian Kofler, Annette Kopp-Schneider, Anna Kreshuk, Tahsin Kurc, Bennett A. Landman, Geert Litjens, Amin Madani, Klaus Maier-Hein, Anne L. Martel, Peter Mattson, Erik Meijering, Bjoern Menze, Karel G. M. Moons, Henning Müller, Brennan Nichyporuk, Felix Nickel, Jens Petersen, Nasir Rajpoot, 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, Paul F. Jäger
The framework was developed in a multi-stage Delphi process and is based on the novel concept of a problem fingerprint - a structured representation of the given problem that captures all aspects that are relevant for metric selection, from the domain interest to the properties of the target structure(s), data set and algorithm output.
1 code implementation • 5 May 2022 • Khanh Nguyen, Huy Hoang Nguyen, Aleksei Tiulpin
CBIR with DNNs is generally solved by minimizing a ranking loss, such as Triplet loss (TL), computed on image representations extracted by a DNN from the original data.
1 code implementation • 26 Jan 2022 • Egor Panfilov, Simo Saarakkala, Miika T. Nieminen, Aleksei Tiulpin
Accurate prediction of knee osteoarthritis (KOA) progression from structural MRI has a potential to enhance disease understanding and support clinical trials.
no code implementations • 8 Jun 2021 • Louis Filstroff, Iiris Sundin, Petrus Mikkola, Aleksei Tiulpin, Juuso Kylmäoja, Samuel Kaski
Active learning is usually applied to acquire labels of informative data points in supervised learning, to maximize accuracy in a sample-efficient way.
2 code implementations • 29 May 2021 • Aleksei Tiulpin, Matthew B. Blaschko
This paper proposes a novel and principled method to tackle this limitation, minimizing an $f$-divergence between the true posterior and a kernel density estimator (KDE) in a function space.
1 code implementation • 12 Apr 2021 • Annika Reinke, Minu D. Tizabi, Carole H. Sudre, Matthias Eisenmann, Tim Rädsch, Michael Baumgartner, Laura Acion, Michela Antonelli, Tal Arbel, Spyridon Bakas, Peter Bankhead, Arriel Benis, Matthew Blaschko, Florian Buettner, M. Jorge Cardoso, Jianxu Chen, Veronika Cheplygina, Evangelia Christodoulou, Beth Cimini, Gary S. Collins, Sandy Engelhardt, Keyvan Farahani, Luciana Ferrer, Adrian Galdran, Bram van Ginneken, Ben Glocker, Patrick Godau, Robert Haase, Fred Hamprecht, Daniel A. Hashimoto, Doreen Heckmann-Nötzel, Peter Hirsch, Michael M. Hoffman, Merel Huisman, Fabian Isensee, Pierre Jannin, Charles E. Kahn, Dagmar Kainmueller, Bernhard Kainz, Alexandros Karargyris, Alan Karthikesalingam, A. Emre Kavur, Hannes Kenngott, Jens Kleesiek, Andreas Kleppe, Sven Kohler, Florian Kofler, Annette Kopp-Schneider, Thijs Kooi, Michal Kozubek, Anna Kreshuk, Tahsin Kurc, Bennett A. Landman, Geert Litjens, Amin Madani, Klaus Maier-Hein, Anne L. Martel, Peter Mattson, Erik Meijering, Bjoern Menze, David Moher, Karel G. M. Moons, Henning Müller, Brennan Nichyporuk, Felix Nickel, M. Alican Noyan, Jens Petersen, Gorkem Polat, Susanne M. Rafelski, Nasir Rajpoot, Mauricio Reyes, Nicola Rieke, Michael Riegler, Hassan Rivaz, Julio Saez-Rodriguez, Clara I. Sánchez, Julien Schroeter, Anindo Saha, M. Alper Selver, Lalith Sharan, Shravya Shetty, Maarten van Smeden, Bram Stieltjes, Ronald M. Summers, Abdel A. Taha, Aleksei Tiulpin, Sotirios A. Tsaftaris, Ben van Calster, Gaël Varoquaux, Manuel Wiesenfarth, Ziv R. Yaniv, Paul Jäger, Lena Maier-Hein
While the importance of automatic image analysis is continuously increasing, recent meta-research revealed major flaws with respect to algorithm validation.
2 code implementations • 8 Apr 2021 • Huy Hoang Nguyen, Simo Saarakkala, Matthew B. Blaschko, Aleksei Tiulpin
We show the effectiveness of our method in predicting the development of structural knee osteoarthritis changes over time.
1 code implementation • 4 Dec 2020 • Abu Mohammed Raisuddin, Elias Vaattovaara, Mika Nevalainen, Marko Nikki, Elina Järvenpää, Kaisa Makkonen, Pekka Pinola, Tuula Palsio, Arttu Niemensivu, Osmo Tervonen, Aleksei Tiulpin
Wrist Fracture is the most common type of fracture with a high incidence rate.
1 code implementation • Preprint on arXiv 2020 • Huy Hoang Nguyen, Simo Saarakkala, Matthew Blaschko, Aleksei Tiulpin
Finally, when compared to a well-tuned fully supervised baseline that yielded a balanced accuracy (BA) of $70. 9\pm0. 8%$ on the test set, Semixup had comparable performance -- BA of $71\pm0. 8%$ $(p=0. 368)$ while requiring $6$ times less labeled data.
no code implementations • 21 Aug 2019 • Neslihan Bayramoglu, Aleksei Tiulpin, Jukka Hirvasniemi, Miika T. Nieminen, Simo Saarakkala
Compared to the current state-of-the-art approaches, our results suggest that the proposed adaptive ROI approach in texture analysis of subchondral bone can increase the diagnostic performance for detecting the presence of radiographic OA.
1 code implementation • 12 Aug 2019 • Egor Panfilov, Aleksei Tiulpin, Stefan Klein, Miika T. Nieminen, Simo Saarakkala
Degeneration of articular cartilage (AC) is actively studied in knee osteoarthritis (OA) research via magnetic resonance imaging (MRI).
no code implementations • 8 Aug 2019 • Roman Solovyev, Iaroslav Melekhov, Timo Lesonen, Elias Vaattovaara, Osmo Tervonen, Aleksei Tiulpin
In contrast to the previous art, we, for the first time, propose to estimate CTR with uncertainty bounds.
4 code implementations • 29 Jul 2019 • Aleksei Tiulpin, Iaroslav Melekhov, Simo Saarakkala
This paper addresses the challenge of localization of anatomical landmarks in knee X-ray images at different stages of osteoarthritis (OA).
1 code implementation • 18 Jul 2019 • Aleksei Tiulpin, Simo Saarakkala
Knee osteoarthritis (OA) is the most common musculoskeletal disease in the world.
1 code implementation • 11 Jul 2019 • Aleksei Tiulpin, Mikko Finnilä, Petri Lehenkari, Heikki J. Nieminen, Simo Saarakkala
In this paper, we present the first application of Deep Learning to PTA-stained osteochondral samples that allows to perform tidemark segmentation in a fully-automatic manner.
no code implementations • 5 May 2019 • Alexander Rakhlin, Aleksei Tiulpin, Alexey A. Shvets, Alexandr A. Kalinin, Vladimir I. Iglovikov, Sergey Nikolenko
Breast cancer is one of the main causes of death worldwide.
1 code implementation • 12 Apr 2019 • Aleksei Tiulpin, Stefan Klein, Sita M. A. Bierma-Zeinstra, Jérôme Thevenot, Esa Rahtu, Joyce van Meurs, Edwin H. G. Oei, Simo Saarakkala
Knee osteoarthritis (OA) is the most common musculoskeletal disease without a cure, and current treatment options are limited to symptomatic relief.
4 code implementations • 19 Oct 2018 • Iaroslav Melekhov, Aleksei Tiulpin, Torsten Sattler, Marc Pollefeys, Esa Rahtu, Juho Kannala
This paper addresses the challenge of dense pixel correspondence estimation between two images.
Ranked #2 on Dense Pixel Correspondence Estimation on HPatches
Dense Pixel Correspondence Estimation Optical Flow Estimation +1
1 code implementation • 29 Oct 2017 • Aleksei Tiulpin, Jérôme Thevenot, Esa Rahtu, Petri Lehenkari, Simo Saarakkala
Here, we also report a radiological OA diagnosis area under the ROC curve of 0. 93.
no code implementations • 31 Jan 2017 • Aleksei Tiulpin, Jérôme Thevenot, Esa Rahtu, Simo Saarakkala
The obtained results for the used datasets show the mean intersection over the union equal to: 0. 84, 0. 79 and 0. 78.