Simon Graham
Simon Graham
在 的电子邮件经过验证
HoVer-Net: Simultaneous Segmentation and Classification of Nuclei in Multi-Tissue Histology Images
S Graham, QD Vu, SEA Raza, A Azam, YW Tsang, JT Kwak, N Rajpoot
arXiv preprint arXiv:1812.06499, 2018
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
MILD-Net: Minimal Information Loss Dilated Network for Gland Instance Segmentation in Colon Histology Images
S Graham, H Chen, J Gamper, Q Dou, PA Heng, D Snead, YW Tsang, ...
Medical Image Analysis 52, 199-211, 2018
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, 53, 2019
A multi-organ nucleus segmentation challenge
N Kumar, R Verma, D Anand, Y Zhou, OF Onder, E Tsougenis, H Chen, ...
IEEE transactions on medical imaging 39 (5), 1380-1391, 2019
Micro-Net: A unified model for segmentation of various objects in microscopy images
SEA Raza, L Cheung, M Shaban, S Graham, D Epstein, S Pelengaris, ...
Medical image analysis 52, 160-173, 2019
Fast scannet: Fast and dense analysis of multi-gigapixel whole-slide images for cancer metastasis detection
H Lin, H Chen, S Graham, Q Dou, N Rajpoot, PA Heng
IEEE transactions on medical imaging 38 (8), 1948-1958, 2019
Cgc-net: Cell graph convolutional network for grading of colorectal cancer histology images
Y Zhou, S Graham, N Alemi Koohbanani, M Shaban, PA Heng, N Rajpoot
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019
SAMS-NET: Stain-aware multi-scale network for instance-based nuclei segmentation in histology images
S Graham, NM Rajpoot
2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018 …, 2018
Pannuke dataset extension, insights and baselines
J Gamper, NA Koohbanani, K Benes, S Graham, M Jahanifar, ...
arXiv preprint arXiv:2003.10778, 2020
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, 1058119, 2018
Dense steerable filter cnns for exploiting rotational symmetry in histology images
S Graham, D Epstein, N Rajpoot
IEEE Transactions on Medical Imaging 39 (12), 4124-4136, 2020
FABnet: Feature attention-based network for simultaneous segmentation of microvessels and nerves in routine histology images of oral cancer
MM Fraz, SA Khurram, S Graham, M Shaban, M Hassan, A Loya, ...
Neural Computing and Applications 32 (14), 9915-9928, 2020
Rota-net: Rotation equivariant network for simultaneous gland and lumen segmentation in colon histology images
S Graham, D Epstein, N Rajpoot
European Congress on Digital Pathology, 109-116, 2019
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, 69-77, 2018
Capturing Cellular Topology in Multi-Gigapixel Pathology Images
W Lu, S Graham, M Bilal, N Rajpoot, F Minhas
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020
MoNuSAC2020: A Multi-organ Nuclei Segmentation and Classification Challenge
R Verma, N Kumar, A Patil, NC Kurian, S Rane, S Graham, QD Vu, ...
IEEE Transactions on Medical Imaging, 2021
Novel deep learning algorithm predicts the status of molecular pathways and key mutations in colorectal cancer from routine histology images
M Bilal, SEA Raza, A Azam, S Graham, M Ilyas, IA Cree, D Snead, ...
medRxiv, 2021
Uncertainty driven pooling network for microvessel segmentation in routine histology images
MM Fraz, M Shaban, S Graham, SA Khurram, NM Rajpoot
Computational pathology and ophthalmic medical image analysis, 156-164, 2018
Development and validation of a weakly supervised deep learning framework to predict the status of molecular pathways and key mutations in colorectal cancer from routine …
M Bilal, SEA Raza, A Azam, S Graham, M Ilyas, IA Cree, D Snead, ...
The Lancet Digital Health, 2021
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