no code implementations • 15 May 2024 • Yujie Xiang, Bojing Liu, Mattias Rantalainen
We propose a multi-model approach, i. e. DeepBlurMM, to alleviate the impact of unsharp image areas and improve the model performance.
1 code implementation • 22 Mar 2024 • Abhinav Sharma, Bojing Liu, Mattias Rantalainen
Deep learning enables the modelling of high-resolution histopathology whole-slide images (WSI).
no code implementations • 7 Jul 2023 • Xiaoyi Ji, Richard Salmon, Nita Mulliqi, Umair Khan, Yinxi Wang, Anders Blilie, Henrik Olsson, Bodil Ginnerup Pedersen, Karina Dalsgaard Sørensen, Benedicte Parm Ulhøi, Svein R Kjosavik, Emilius AM Janssen, Mattias Rantalainen, Lars Egevad, Pekka Ruusuvuori, Martin Eklund, Kimmo Kartasalo
The potential of artificial intelligence (AI) in digital pathology is limited by technical inconsistencies in the production of whole slide images (WSIs), leading to degraded AI performance and posing a challenge for widespread clinical application as fine-tuning algorithms for each new site is impractical.
1 code implementation • 29 May 2023 • Philippe Weitz, Masi Valkonen, Leslie Solorzano, Circe Carr, Kimmo Kartasalo, Constance Boissin, Sonja Koivukoski, Aino Kuusela, Dusan Rasic, Yanbo Feng, Sandra 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
The alignment of tissue between histopathological whole-slide-images (WSI) is crucial for research and clinical applications.
no code implementations • 12 Mar 2023 • Philippe Weitz, Viktoria Sartor, Balazs Acs, Stephanie Robertson, Daniel Budelmann, Johan Hartman, Mattias Rantalainen
This indicates that WSI registration has the potential to reduce the need for IHC-specific annotations.
no code implementations • 24 Nov 2022 • 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
In particular, there are no large, high quality publicly available data sets with WSIs of matching IHC and H&E-stained tissue sections.
no code implementations • 27 Jun 2021 • Bojing Liu, Yinxi Wang, Philippe Weitz, Johan Lindberg, Johan Hartman, Lars Egevad, Henrik Grönberg, Martin Eklund, Mattias Rantalainen
As a proof-of-principle, we developed and validated a deep convolutional neural network model to distinguish between morphological patterns in benign prostate biopsy whole slide images from men with and without established cancer.
1 code implementation • 19 Apr 2021 • Philippe Weitz, Yinxi Wang, Kimmo Kartasalo, Lars Egevad, Johan Lindberg, Henrik Grönberg, Martin Eklund, Mattias Rantalainen
Molecular phenotyping by gene expression profiling is common in contemporary cancer research and in molecular diagnostics.
no code implementations • 18 Sep 2020 • Yinxi Wang, Kimmo Kartasalo, Masi Valkonen, Christer Larsson, Pekka Ruusuvuori, Johan Hartman, Mattias Rantalainen
The relationship between morphology and molecular phenotype has a potential to be exploited for prediction of the molecular phenotype from the morphology visible in histopathology images.
no code implementations • 2 Jul 2019 • 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
We additionally evaluated grading performance on 87 biopsies individually graded by 23 experienced urological pathologists from the International Society of Urological Pathology.