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Kimmo Kartasalo
Researcher at University of Tampere
Publications - 42
Citations - 3203
Kimmo Kartasalo is an academic researcher from University of Tampere. The author has contributed to research in topics: Computer science & Medicine. The author has an hindex of 11, co-authored 31 publications receiving 1879 citations. Previous affiliations of Kimmo Kartasalo include HTW Berlin - University of Applied Sciences & Karolinska Institutet.
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Journal ArticleDOI
Diagnostic Assessment of Deep Learning Algorithms for Detection of Lymph Node Metastases in Women With Breast Cancer.
Babak Ehteshami Bejnordi,Mitko Veta,Paul J. van Diest,Bram van Ginneken,Nico Karssemeijer,Geert Litjens,Jeroen van der Laak,Meyke Hermsen,Quirine F. Manson,Maschenka Balkenhol,Oscar Geessink,N. Stathonikos,Marcory C. R. F. van Dijk,Peter Bult,Francisco Beca,Andrew H. Beck,Dayong Wang,Aditya Khosla,Rishab Gargeya,Humayun Irshad,Aoxiao Zhong,Qi Dou,Qi Dou,Quanzheng Li,Hao Chen,Huangjing Lin,Pheng-Ann Heng,Christian Haß,Elia Bruni,Quincy Wong,Ugur Halici,Mustafa Umit Oner,Rengul Cetin-Atalay,Matt Berseth,Vitali Khvatkov,Alexei Vylegzhanin,Oren Kraus,Muhammad Shaban,Nasir M. Rajpoot,Nasir M. Rajpoot,Ruqayya Awan,Korsuk Sirinukunwattana,Talha Qaiser,Yee-Wah Tsang,David Tellez,Jonas Annuscheit,Peter Hufnagl,Mira Valkonen,Kimmo Kartasalo,Kimmo Kartasalo,Leena Latonen,Pekka Ruusuvuori,Pekka Ruusuvuori,Kaisa Liimatainen,Shadi Albarqouni,Bharti Mungal,Ami George,Stefanie Demirci,Nassir Navab,Seiryo Watanabe,Shigeto Seno,Yoichi Takenaka,Hideo Matsuda,Hady Ahmady Phoulady,Vassili Kovalev,A. Kalinovsky,Vitali Liauchuk,Gloria Bueno,M. Milagro Fernández-Carrobles,Ismael Serrano,Oscar Deniz,Daniel Racoceanu,Daniel Racoceanu,Rui Venâncio +73 more
TL;DR: In the setting of a challenge competition, some deep learning algorithms achieved better diagnostic performance than a panel of 11 pathologists participating in a simulation exercise designed to mimic routine pathology workflow; algorithm performance was comparable with an expert pathologist interpreting whole-slide images without time constraints.
Journal ArticleDOI
Artificial intelligence for diagnosis and grading of prostate cancer in biopsies: a population-based, diagnostic study.
Peter Ström,Kimmo Kartasalo,Henrik Olsson,Leslie Solorzano,Brett Delahunt,Daniel M. Berney,David G. Bostwick,Andrew Evans,David J. Grignon,Peter A. Humphrey,Kenneth A. Iczkowski,James G. Kench,Glen Kristiansen,Theodorus 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 Lindskog,Pekka Ruusuvuori,Carolina Wählby,Henrik Grönberg,Mattias Rantalainen,Lars Egevad,Martin Eklund +31 more
TL;DR: An artificial intelligence system can be trained to detect and grade cancer in prostate needle biopsy samples at a ranking comparable to that of international experts in prostate pathology.
Journal ArticleDOI
Deep Learning in Image Cytometry: A Review
Anindya Gupta,Philip J. Harrison,Håkan Wieslander,Nicolas Pielawski,Kimmo Kartasalo,Kimmo Kartasalo,Gabriele Partel,Leslie Solorzano,Amit Suveer,Anna H. Klemm,Ola Spjuth,Ida-Maria Sintorn,Carolina Wählby +12 more
TL;DR: This review focuses on deep learning and how it is applied to microscopy image data of cells and tissue samples, and gives the reader an overview of the key concepts of neural networks, and an understanding of how deep learning differs from more classical approaches for extracting information from image data.
Journal ArticleDOI
Artificial intelligence for diagnosis and Gleason grading of prostate cancer: the PANDA challenge
Wouter Bulten,Kimmo Kartasalo,Po-Hsuan Cameron Chen,Peter Ström,Hans Pinckaers,Kunal Nagpal,Yuannan Cai,David F. Steiner,Hester van Boven,Rob Vink,Christina A. Hulsbergen-van de Kaa,J. A. W. M. van der Laak,Mahul B. Amin,Andrew Evans,Theodorus van der Kwast,Robert Allan,Peter A. Humphrey,Henrik Grönberg,Hemamali Samaratunga,Brett Delahunt,Toyonori Tsuzuki,Tomi Häkkinen,Lars Egevad,Maggie Demkin,Sohier Dane,Fraser Tan,Masi Valkonen,Greg S. Corrado,Lily Peng,Craig H. Mermel,Pekka Ruusuvuori,Geert Litjens,Martin Eklund,Américo Brilhante,Asli Cakir,Xavier Farré,Katerina Geronatsiou,Vincent Molinié,Guilherme Pereira,Paromita Roy,Günter Saile,Paulo Guilherme de Oliveira Salles,Ewout Schaafsma,Joëlle Tschui,Jorge Billoch-Lima,Emíio M. Pereira,Ming Zhou,Shujun He,Sejun Song,Qing Sun,Hiroshi Yoshihara,Taiki Yamaguchi,Kosaku Ono,Tao Shen,Jianyi Ji,Arnaud Roussel,Kairong Zhou,Tianrui Chai,Nina Weng,Dmitry A. Grechka,Maxim V. Shugaev,Raphael Kiminya,Vassili Kovalev,Dmitry Voynov,V Malyshev,E. Lapo,Manolo Quispe Campos,Noriaki Ota,Shinsuke Yamaoka,Yusuke Fujimoto,Kentaro Yoshioka,Joni Juvonen,Mikko Tukiainen,Antti Karlsson,Rui Guo,Chia-Lun Hsieh,I S Zubarev,Habib S. T. Bukhar,Wenyuan Li,Jiayun Li,William Speier,Corey W. Arnold,Kyungdoc Kim,Byeonguk Bae,Yeong Won Kim,Hong-Seok Lee,Jeonghyuk Park +86 more
TL;DR: The PANDA challenge as mentioned in this paper was organized by 1,290 developers to catalyze development of reproducible AI algorithms for Gleason grading using 10,616 digitized prostate biopsies.
Journal ArticleDOI
ANHIR: Automatic Non-Rigid Histological Image Registration Challenge
Jiri Borovec,Jan Kybic,Ignacio Arganda-Carreras,Dmitry V. Sorokin,Gloria Bueno,Alexander Khvostikov,Spyridon Bakas,Eric Chang,Stefan Heldmann,Kimmo Kartasalo,Leena Latonen,Johannes Lotz,Michelle Noga,Sarthak Pati,Kumaradevan Punithakumar,Pekka Ruusuvuori,Andrzej Skalski,Nazanin Tahmasebi,Masi Valkonen,Ludovic Venet,Yizhe Wang,Nick Weiss,Marek Wodzinski,Yu Xiang,Yan Xu,Yan Yan,Paul A. Yushkevich,Shengyu Zhao,Arrate Muñoz-Barrutia +28 more
TL;DR: The best methods used coarse but robust initial alignment, followed by non-rigid registration, used multiresolution, and were carefully tuned for the data at hand, which outperformed off-the-shelf methods.