| 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 | 3010 | 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 | 525 | 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 | 302 | 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 | 188 | 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 | 124 | 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 | 85 | 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 | 68 | 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 | 57 | 2017 |
| 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 | 52 | 2021 |
| 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 |
| 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 (1), 2190657, 2018 | 44 | 2018 |
| 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 | 35 | 2022 |
| 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 | 33 | 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 | 31 | 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 |
| 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 | 21 | 2021 |
| 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 | 18 | 2022 |
| 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 | 16 | 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 | 14 | 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 | 14 | 2017 |
Pekka RuusuvuoriUniversity of Turku在 utu.fi 的电子邮件经过验证
