Kimmo Kartasalo

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Pekka RuusuvuoriUniversity of TurkuDirección de correo verificada de utu.fi
Leena LatonenUniversity of Eastern FinlandDirección de correo verificada de uef.fi
Matti NykterTampere UniversityDirección de correo verificada de tuni.fi
Brett DelahuntDirección de correo verificada de otago.ac.nz
Hemamali SamaratungaAquesta pathologyDirección de correo verificada de aquesta.com.au
Mattias RantalainenAssociate professor, Karolinska Institutet, SwedenDirección de correo verificada de ki.se
Carolina WählbyProfessor of Quantitative Microscopy, SciLifeLab and Dept. IT, Uppsala University, SwedenDirección de correo verificada de it.uu.se
Leslie SolorzanoPostDoc, Medical Epidemiology and Biostatistics, Karolinska InstitutetDirección de correo verificada de ki.se
Peter StrömKarolinska InstitutetDirección de correo verificada de ki.se
Antti YlipääGenevia TechnologiesDirección de correo verificada de geneviatechnologies.com
Ola SpjuthProfessor at Department of Pharmaceutical Biosciences, Uppsala UniversityDirección de correo verificada de farmbio.uu.se
Pasi KallioProfessor in Biomedical Sciences and EngineeringDirección de correo verificada de tuni.fi
serdar karakurtselçuk üniversitesiDirección de correo verificada de selcuk.edu.tr
Olli Yli-HarjaTampere University, Faculty of Medicine and Health TechnologyDirección de correo verificada de tuni.fi
Johan HartmanDept of Oncology-Pathology, Karolinska InstitutetDirección de correo verificada de ki.se
Ida-Maria SintornDept. IT, Uppsala University & Vironova ABDirección de correo verificada de vironova.com
Amit SuveerNordicVision AI (self-employed)Dirección de correo verificada de nordicvision.ai
Anindya GuptaLead computer Vision Data Scientist, Stora EnsoDirección de correo verificada de storaenso.com
Philip John HarrisonUppsala UniversityDirección de correo verificada de farmbio.uu.se
Nicolas PielawskiUppsala UniversityDirección de correo verificada de it.uu.se

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Kimmo Kartasalo

Postdoctoral researcher, Karolinska institutet

Dirección de correo verificada de ki.se

Image analysis Machine learning Bioimage informatics Digital pathology Computational pathology


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	Año
Diagnostic assessment of deep learning algorithms for detection of lymph node metastases in women with breast cancer BE Bejnordi, M Veta, PJ Van Diest, B Van Ginneken, N Karssemeijer, ... Jama 318 (22), 2199-2210, 2017	2898	2017
Artificial intelligence for diagnosis and grading of prostate cancer in biopsies: a population-based, diagnostic study P Ström, K Kartasalo, H Olsson, L Solorzano, B Delahunt, DM Berney, ... The Lancet Oncology 21 (2), 222-232, 2020	486	2020
Artificial intelligence for diagnosis and Gleason grading of prostate cancer: the PANDA challenge W Bulten, K Kartasalo, PHC Chen, P Ström, H Pinckaers, K Nagpal, Y Cai, ... Nature medicine 28 (1), 154-163, 2022	260	2022
Deep learning in image cytometry: a review A Gupta, PJ Harrison, H Wieslander, N Pielawski, K Kartasalo, G Partel, ... Cytometry Part A 95 (4), 366-380, 2019	187	2019
ANHIR: automatic non-rigid histological image registration challenge J Borovec, J Kybic, I Arganda-Carreras, DV Sorokin, G Bueno, ... IEEE transactions on medical imaging 39 (10), 3042-3052, 2020	116	2020
Transcriptome Sequencing Reveals PCAT5 as a Novel ERG-Regulated Long Noncoding RNA in Prostate Cancer A Ylipää, K Kivinummi, A Kohvakka, M Annala, L Latonen, M Scaravilli, ... Cancer research 75 (19), 4026-4031, 2015	84	2015
CytoSpectre: a tool for spectral analysis of oriented structures on cellular and subcellular levels K Kartasalo, RP Pölönen, M Ojala, J Rasku, J Lekkala, K Aalto-Setälä, ... BMC bioinformatics 16, 1-23, 2015	63	2015
Metastasis detection from whole slide images using local features and random forests M Valkonen, K Kartasalo, K Liimatainen, M Nykter, L Latonen, ... Cytometry Part A 91 (6), 555-565, 2017	54	2017
Comparative analysis of tissue reconstruction algorithms for 3D histology K Kartasalo, L Latonen, J Vihinen, T Visakorpi, M Nykter, P Ruusuvuori Bioinformatics 34 (17), 3013-3021, 2018	48	2018
Predicting Molecular Phenotypes from Histopathology Images: A Transcriptome-Wide Expression–Morphology Analysis in Breast Cancer Y Wang, K Kartasalo, P Weitz, B Ács, M Valkonen, C Larsson, ... Cancer Research 81 (19), 5115–5126, 2021	45	2021
Focal adhesion kinase and ROCK signaling are switch-like regulators of human adipose stem cell differentiation towards osteogenic and adipogenic lineages L Hyväri, M Ojansivu, M Juntunen, K Kartasalo, S Miettinen, S Vanhatupa Stem cells international 2018, 2018	43	2018
Identification of areas of grading difficulties in prostate cancer and comparison with artificial intelligence assisted grading L Egevad, D Swanberg, B Delahunt, P Ström, K Kartasalo, H Olsson, ... Virchows Archiv 477, 777-786, 2020	32	2020
Artificial intelligence for diagnosis and Gleason grading of prostate cancer in biopsies—current status and next steps K Kartasalo, W Bulten, B Delahunt, PHC Chen, H Pinckaers, H Olsson, ... European Urology Focus 7 (4), 687-691, 2021	27	2021
Estimating diagnostic uncertainty in artificial intelligence assisted pathology using conformal prediction H Olsson, K Kartasalo, N Mulliqi, M Capuccini, P Ruusuvuori, ... Nature communications 13 (1), 7761, 2022	24	2022
Morphological features extracted by AI associated with spatial transcriptomics in prostate cancer E Chelebian, C Avenel, K Kartasalo, M Marklund, A Tanoglidi, T Mirtti, ... Cancers 13 (19), 4837, 2021	22	2021
A durable and biocompatible ascorbic acid-based covalent coating method of polydimethylsiloxane for dynamic cell culture J Leivo, S Virjula, S Vanhatupa, K Kartasalo, J Kreutzer, S Miettinen, ... Journal of The Royal Society Interface 14 (132), 20170318, 2017	22	2017
Transcriptome-wide prediction of prostate cancer gene expression from histopathology images using co-expression-based convolutional neural networks P Weitz, Y Wang, K Kartasalo, L Egevad, J Lindberg, H Grönberg, ... Bioinformatics 38 (13), 3462-3469, 2022	16	2022
Dual structured convolutional neural network with feature augmentation for quantitative characterization of tissue histology M Valkonen, K Kartasalo, K Liimatainen, M Nykter, L Latonen, ... Proceedings of the IEEE International Conference on Computer Vision …, 2017	15	2017
Virtual reality for 3D histology: multi-scale visualization of organs with interactive feature exploration K Liimatainen, L Latonen, M Valkonen, K Kartasalo, P Ruusuvuori BMC cancer 21, 1-14, 2021	14	2021
Detection of perineural invasion in prostate needle biopsies with deep neural networks K Kartasalo, P Ström, P Ruusuvuori, H Samaratunga, B Delahunt, ... Virchows Archiv 481 (1), 73-82, 2022	11	2022

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