Mattias Rantalainen

According to our database, Mattias Rantalainen authored at least 16 papers between 2008 and 2024.

Collaborative distances:

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

2024

The ACROBAT 2022 challenge: Automatic registration of breast cancer tissue.

Philippe Weitz, Masi Valkonen, Leslie Solorzano, Circe Carr, Kimmo Kartasalo, Constance Boissin, Sonja Koivukoski, Aino Kuusela, Dusan Rasic, Yanbo Feng, Sandra Kristiane Sinius Pouplier, Abhinav Sharma, Kajsa Ledesma Eriksson, Stephanie Robertson, Christian Marzahl, Chandler D. Gatenbee, Alexander R. A. Anderson, Marek Wodzinski, Artur Jurgas, Niccolò Marini, Manfredo Atzori, Henning Müller, Daniel Budelmann, Nick Weiss, Stefan Heldmann, Johannes Lotz, Jelmer M. Wolterink, Bruno De Santi, Abhijeet Patil, Amit Sethi, Satoshi Kondo, Satoshi Kasai, Kousuke Hirasawa, Mahtab Farrokh, Neeraj Kumar, Russell Greiner, Leena Latonen, Anne-Vibeke Laenkholm, Johan Hartman, Pekka Ruusuvuori, Mattias Rantalainen

Medical Image Anal., 2024

Deep Blur Multi-Model (DeepBlurMM) - a strategy to mitigate the impact of image blur on deep learning model performance in histopathology image analysis.

Yujie Xiang, Bojing Liu, Mattias Rantalainen

CoRR, 2024

WEEP: A method for spatial interpretation of weakly supervised CNN models in computational pathology.

Abhinav Sharma, Bojing Liu, Mattias Rantalainen

CoRR, 2024

2023

Physical Color Calibration of Digital Pathology Scanners for Robust Artificial Intelligence Assisted Cancer Diagnosis.

Xiaoyi Ji, Richard Salmon, Nita Mulliqi, Umair Khan, Yinxi Wang, Anders Blilie, Henrik Olsson, Bodil Ginnerup Pedersen, Karina Dalsgaard Sørensen, Benedicte Parm Ulhøi, Svein Reidar Kjosavik, Emilius A. M. Janssen, Mattias Rantalainen, Lars Egevad, Pekka Ruusuvuori, Martin Eklund, Kimmo Kartasalo

CoRR, 2023

Increasing the usefulness of already existing annotations through WSI registration.

Philippe Weitz, Viktoria Sartor, Balazs Acs, Stephanie Robertson, Daniel Budelmann, Johan Hartman, Mattias Rantalainen

CoRR, 2023

2022

ACROBAT - a multi-stain breast cancer histological whole-slide-image data set from routine diagnostics for computational pathology.

Philippe Weitz, Masi Valkonen, Leslie Solorzano, Circe Carr, Kimmo Kartasalo, Constance Boissin, Sonja Koivukoski, Aino Kuusela, Dusan Rasic, Yanbo Feng, Sandra Kristiane Sinius Pouplier, Abhinav Sharma, Kajsa Ledesma Eriksson, Leena Latonen, Anne-Vibeke Laenkholm, Johan Hartman, Pekka Ruusuvuori, Mattias Rantalainen

CoRR, 2022

Transcriptome-wide prediction of prostate cancer gene expression from histopathology images using co-expression-based convolutional neural networks.

Philippe Weitz, Yinxi Wang, Kimmo Kartasalo, Lars Egevad, Johan Lindberg, Henrik Grönberg, Martin Eklund, Mattias Rantalainen

Bioinform., 2022

2021

Using deep learning to detect patients at risk for prostate cancer despite benign biopsies.

Bojing Liu, Yinxi Wang, Philippe Weitz, Johan Lindberg, Lars Egevad, Henrik Grönberg, Martin Eklund, Mattias Rantalainen

CoRR, 2021

An investigation of attention mechanisms in histopathology whole-slide-image analysis for regression objectives.

Philippe Weitz, Yinxi Wang, Johan Hartman, Mattias Rantalainen

Proceedings of the IEEE/CVF International Conference on Computer Vision Workshops, 2021

2020

Predicting molecular phenotypes from histopathology images: a transcriptome-wide expression-morphology analysis in breast cancer.

Yinxi Wang, Kimmo Kartasalo, Masi Valkonen, Christer Larsson, Pekka Ruusuvuori, Johan Hartman, Mattias Rantalainen

CoRR, 2020

2019

Pathologist-Level Grading of Prostate Biopsies with Artificial Intelligence.

Peter Ström, Kimmo Kartasalo, Henrik Olsson, Leslie Solorzano, Brett Delahunt, Daniel M. Berney, David G. Bostwick, Andrew J. Evans, David J. Grignon, Peter A. Humphrey, Kenneth A. Iczkowski, James G. Kench, Glen Kristiansen, Theodorus H. van der Kwast, Katia R. M. Leite, Jesse K. McKenney, Jon Oxley, Chin-Chen Pan, Hemamali Samaratunga, John R. Srigley, Hiroyuki Takahashi, Toyonori Tsuzuki, Murali Varma, Ming Zhou, Johan Lindberg, Cecilia Bergström, Pekka Ruusuvuori, Carolina Wählby, Henrik Grönberg, Mattias Rantalainen, Lars Egevad, Martin Eklund

CoRR, 2019

2018

Isoform-level gene expression patterns in single-cell RNA-sequencing data.

Trung-Nghia Vu, Quin F. Wills, Krishna R. Kalari, Nifang Niu, Liewei Wang, Yudi Pawitan, Mattias Rantalainen

Bioinform., 2018

2017

E-Science technologies in a workflow for personalized medicine using cancer screening as a case study.

Ola Spjuth, Andreas Karlsson, Mark Clements, Keith Humphreys, Emma Ivansson, Jim Dowling, Martin Eklund, Alexandra Jauhiainen, Kamila Czene, Henrik Gronberg, Pär Sparén, Fredrik Wiklund, Abbas Cheddad, þorgerður Pálsdóttir, Mattias Rantalainen, Linda Abrahamsson, Erwin Laure, Jan-Eric Litton, Juni Palmgren

J. Am. Medical Informatics Assoc., 2017

2016

Beta-Poisson model for single-cell RNA-seq data analyses.

Trung-Nghia Vu, Quin F. Wills, Krishna R. Kalari, Nifang Niu, Liewei Wang, Mattias Rantalainen, Yudi Pawitan

Bioinform., 2016

2008

Piecewise multivariate modelling of sequential metabolic profiling data.

Mattias Rantalainen, Olivier Cloarec, Timothy M. D. Ebbels, Torbjörn Lundstedt, Jeremy K. Nicholson, Elaine Holmes, Johan Trygg

BMC Bioinform., 2008

K-OPLS package: Kernel-based orthogonal projections to latent structures for prediction and interpretation in feature space.

Max Bylesjö, Mattias Rantalainen, Jeremy K. Nicholson, Elaine Holmes, Johan Trygg

BMC Bioinform., 2008