| Mask-RCNN and U-net ensembled for nuclei segmentation AO Vuola, SU Akram, J Kannala 2019 IEEE 16th international symposium on biomedical imaging (ISBI 2019 …, 2019 | 183 | 2019 |
| Cell segmentation proposal network for microscopy image analysis SU Akram, J Kannala, L Eklund, J Heikkilä Deep Learning and Data Labeling for Medical Applications: First …, 2016 | 104 | 2016 |
| A novel human leiomyoma tissue derived matrix for cell culture studies T Salo, M Sutinen, E Hoque Apu, E Sundquist, NK Cervigne, ... Bmc Cancer 15 (1), 1-16, 2015 | 94 | 2015 |
| Generalizable pedestrian detection: The elephant in the room I Hasan, S Liao, J Li, SU Akram, L Shao Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 78 | 2021 |
| HNF1B controls epithelial organization and cell polarity during ureteric bud branching and collecting duct morphogenesis A Desgrange, C Heliot, I Skovorodkin, SU Akram, J Heikkilä, ... Development 144 (24), 4704-4719, 2017 | 47 | 2017 |
| A deep learning-based automated CT segmentation of prostate cancer anatomy for radiation therapy planning-a retrospective multicenter study T Kiljunen, S Akram, J Niemelä, E Löyttyniemi, J Seppälä, J Heikkilä, ... Diagnostics 10 (11), 959, 2020 | 35 | 2020 |
| Joint cell segmentation and tracking using cell proposals SU Akram, J Kannala, L Eklund, J Heikkilä 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI), 920-924, 2016 | 30 | 2016 |
| Cell tracking via proposal generation and selection SU Akram, J Kannala, L Eklund, J Heikkilä arXiv preprint arXiv:1705.03386, 2017 | 26 | 2017 |
| Pedestrian detection: The elephant in the room I Hasan, S Liao, J Li, SU Akram, L Shao arXiv preprint arXiv:2003.08799 6 (7), 2020 | 25 | 2020 |
| Leveraging unlabeled whole-slide-images for mitosis detection SU Akram, T Qaiser, S Graham, J Kannala, J Heikkilä, N Rajpoot Computational Pathology and Ophthalmic Medical Image Analysis: First …, 2018 | 25 | 2018 |
| Cell proposal network for microscopy image analysis SU Akram, J Kannala, L Eklund, J Heikkilä 2016 IEEE International Conference on Image Processing (ICIP), 3199-3203, 2016 | 23 | 2016 |
| Desmoglein 3–Influence on oral carcinoma cell migration and invasion EH Apu, SU Akram, J Rissanen, H Wan, T Salo Experimental Cell Research 370 (2), 353-364, 2018 | 22 | 2018 |
| Novel fixed z-direction (FiZD) kidney primordia and an organoid culture system for time-lapse confocal imaging U Saarela, SU Akram, A Desgrange, A Rak-Raszewska, J Shan, ... Development 144 (6), 1113-1117, 2017 | 21 | 2017 |
| Pedestrian Detection: Domain Generalization, CNNs, Transformers and Beyond I Hasan, S Liao, J Li, SU Akram, L Shao arXiv preprint arXiv:2201.03176, 2022 | 15 | 2022 |
| Visual recognition of isolated swedish sign language signs S Akram, J Beskow, H Kjellstrom arXiv preprint arXiv:1211.3901, 2012 | 8 | 2012 |
| Visual Recognition of Isolated Swedish Sign Language Signs S Akram School of Computer Science and Communication, KTH - Royal Institute of …, 2012 | 8 | 2012 |
| Segmentation of cells from spinning disk confocal images using a multi-stage approach SU Akram, J Kannala, M Kaakinen, L Eklund, J Heikkilä Computer Vision--ACCV 2014: 12th Asian Conference on Computer Vision …, 2015 | 6 | 2015 |
| Bridging the gap between paired and unpaired medical image translation P Paavilainen, SU Akram, J Kannala Deep Generative Models, and Data Augmentation, Labelling, and Imperfections …, 2021 | 5 | 2021 |
| Autosegmentation based on different-sized training datasets of consistently-curated volumes and impact on rectal contours in prostate cancer radiation therapy CE Olsson, R Suresh, J Niemelä, SU Akram, A Valdman Physics and Imaging in Radiation Oncology 22, 67-72, 2022 | 3 | 2022 |
| The effect of hydrodynamic conditions on the selective flotation of fully liberated low grade copper-nickel ore H Kumar, K Luolavirta, SU Akram, H Mehmood, S Luukkanen Minerals 11 (3), 328, 2021 | 2 | 2021 |
Juho KannalaAssistant Professor, Aalto University, FinlandVerified email at aalto.fi
