no code implementations • 25 Oct 2023 • Fabi Prezja, Leevi Annala, Sampsa Kiiskinen, Suvi Lahtinen, Timo Ojala, Pekka Ruusuvuori, Teijo Kuopio
However, recent research highlights the potential of convolutional neural networks (CNNs) in facilitating the extraction of clinically relevant biomarkers from these readily available images.
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 • 30 Dec 2022 • Liisa Petäinen, Juha P. Väyrynen, Pekka Ruusuvuori, Ilkka Pölönen, Sami Äyrämö, Teijo Kuopio
The method is based on convolutional neural networks which were trained to classify colorectal cancer tissue in hematoxylin-eosin stained samples into three classes: stroma, tumor and other.
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.
1 code implementation • 26 Aug 2022 • Joel Honkamaa, Umair Khan, Sonja Koivukoski, Mira Valkonen, Leena Latonen, Pekka Ruusuvuori, Pekka Marttinen
Cross-modality image synthesis is an active research topic with multiple medical clinically relevant applications.
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 • 3 Apr 2020 • Peter Ström, Kimmo Kartasalo, Pekka Ruusuvuori, Henrik Grönberg, Hemamali Samaratunga, Brett Delahunt, Toyonori Tsuzuki, Lars Egevad, Martin Eklund
Results: For the detection of PNI in prostate biopsy cores the network had an estimated area under the receiver operating characteristics curve of 0. 98 (95% CI 0. 97-0. 99) based on 106 PNI positive cores and 1, 652 PNI negative cores in the independent test set.
1 code implementation • 24 Mar 2020 • Kaisa Liimatainen, Leena Latonen, Masi Valkonen, Kimmo Kartasalo, Pekka Ruusuvuori
In this work, we used whole mouse prostates (organ level) with prostate cancer tumors (sub-organ objects of interest) as example cases, and included quantitative histological features relevant for tumor biology in the VR model.
Graphics Image and Video Processing
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.