| 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 |
| Predicting breast tumor proliferation from whole-slide images: the TUPAC16 challenge M Veta, YJ Heng, N Stathonikos, BE Bejnordi, F Beca, T Wollmann, ... Medical image analysis 54, 111-121, 2019 | 284 | 2019 |
| Methods for segmentation and classification of digital microscopy tissue images QD Vu, S Graham, T Kurc, MNN To, M Shaban, T Qaiser, NA Koohbanani, ... Frontiers in bioengineering and biotechnology 7, 433738, 2019 | 258 | 2019 |
| Fast and accurate tumor segmentation of histology images using persistent homology and deep convolutional features T Qaiser, YW Tsang, D Taniyama, N Sakamoto, K Nakane, D Epstein, ... Medical image analysis 55, 1-14, 2019 | 175 | 2019 |
| Her2 Challenge Contest: A Detailed Assessment of Automated Her2 Scoring Algorithms in Whole Slide Images of Breast Cancer Tissues T Qaiser, A Mukherjee, SD Munugoti, V Tallam, T Pitkäaho, T Lehtimäki, ... Histopathology 72 (2), 2018 | 140 | 2018 |
| Learning Where to See: A Novel Attention Model for Automated Immunohistochemical Scoring T Qaiser, NM Rajpoot IEEE transactions on medical imaging, 2019 | 79 | 2019 |
| Persistent homology for fast tumor segmentation in whole slide histology images T Qaiser, K Sirinukunwattana, K Nakane, YW Tsang, D Epstein, N Rajpoot Procedia Computer Science 90, 119-124, 2016 | 76 | 2016 |
| Classification of lung cancer histology images using patch-level summary statistics S Graham, M Shaban, T Qaiser, NA Koohbanani, SA Khurram, N Rajpoot Medical Imaging 2018: Digital Pathology 10581, 327-334, 2018 | 60 | 2018 |
| 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 | 31 | 2018 |
| Tumor segmentation in whole slide images using persistent homology and deep convolutional features T Qaiser, YW Tsang, D Epstein, N Rajpoot Medical Image Understanding and Analysis: 21st Annual Conference, MIUA 2017 …, 2017 | 25 | 2017 |
| Investigating the effect of various augmentations on the input data fed to a convolutional neural network for the task of mammographic mass classification A Hamidinekoo, Z Suhail, T Qaiser, R Zwiggelaar Medical Image Understanding and Analysis: 21st Annual Conference, MIUA 2017 …, 2017 | 21 | 2017 |
| Usability of deep learning and H&E images predict disease outcome-emerging tool to optimize clinical trials T Qaiser, CY Lee, M Vandenberghe, J Yeh, MA Gavrielides, J Hipp, ... NPJ precision oncology 6 (1), 37, 2022 | 19 | 2022 |
| Nucleus classification in histology images using message passing network T Hassan, S Javed, A Mahmood, T Qaiser, N Werghi, N Rajpoot Medical Image Analysis 79, 102480, 2022 | 16 | 2022 |
| Multiple instance learning with auxiliary task weighting for multiple myeloma classification T Qaiser, S Winzeck, T Barfoot, T Barwick, SJ Doran, MF Kaiser, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2021: 24th …, 2021 | 11 | 2021 |
| Hybrid aggregation network for survival analysis from whole slide histopathological images JR Chang, CY Lee, CC Chen, J Reischl, T Qaiser, CY Yeh Medical Image Computing and Computer Assisted Intervention–MICCAI 2021: 24th …, 2021 | 10 | 2021 |
| Knowledge distillation in histology landscape by multi-layer features supervision S Javed, A Mahmood, T Qaiser, N Werghi IEEE Journal of Biomedical and Health Informatics 27 (4), 2037-2046, 2023 | 9 | 2023 |
| Development of machine learning support for reading whole body diffusion-weighted MRI (WB-MRI) in myeloma for the detection and quantification of the extent of disease before … L Satchwell, L Wedlake, E Greenlay, X Li, C Messiou, B Glocker, ... BMJ open 12 (10), e067140, 2022 | 7 | 2022 |
| HydraMix-Net: a deep multi-task semi-supervised learning approach for cell detection and classification RMS Bashir, T Qaiser, SEA Raza, NM Rajpoot Interpretable and Annotation-Efficient Learning for Medical Image Computing …, 2020 | 7 | 2020 |
| Digital tumor-collagen proximity signature predicts survival in diffuse large B-cell lymphoma T Qaiser, M Pugh, S Margielewska, R Hollows, P Murray, N Rajpoot Digital Pathology: 15th European Congress, ECDP 2019, Warwick, UK, April 10 …, 2019 | 7 | 2019 |
| Glyoxalase 1 copy number variation in patients with well differentiated gastro-entero-pancreatic neuroendocrine tumours (GEP-NET) M Xue, A Shafie, T Qaiser, NM Rajpoot, G Kaltsas, S James, ... Oncotarget 8 (44), 76961, 2017 | 7 | 2017 |
Nasir M. RajpootTissue Image Analytics (TIA) Centre, University of WarwickVahvistettu sähköpostiosoite verkkotunnuksessa warwick.ac.uk
