Azam Hamidinekoo
Azam Hamidinekoo
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Zitiert von
Zitiert von
Deep Learning in Mammography and Breast Histology, an Overview and Future Trends
A Hamidinekoo, E Denton, A Rampun, K Honnor, R Zwiggelaar
Medical Image Analysis 47, 45 – 67, 2018
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
Annual Conference on Medical Image Understanding and Analysis, 398-409, 2017
Comparing the performance of various deep networks for binary classification of breast tumours
A Hamidinekoo, Z Suhail, E Denton, R Zwiggelaar
14th International Workshop on Breast Imaging (IWBI 2018) 10718, 1071807, 2018
Manifold learning based registration algorithms applied to multimodal images
MF Azampour, A Ghaffari, A Hamidinekoo, E Fatemizadeh
Engineering in Medicine and Biology Society (EMBC), 2014 36th Annual …, 2014
Using a conditional Generative Adversarial Network (cGAN) for Prostate Segmentation
A Grall, A Hamidinekoo, P Malcolm, R Zwiggelaar
23rd Conference on Medical Image Understanding and Analysis, 2019
Distributed rough set based feature selection approach to analyse deep and hand-crafted features for mammography mass classification
A Hamidinekoo, ZC Dagdia, Z Suhail, R Zwiggelaar
2018 IEEE International Conference on Big Data (Big Data), 2423-2432, 2018
DeepPod: a convolutional neural network based quantification of fruit number in Arabidopsis
A Hamidinekoo, GA Garzón-Martínez, M Ghahremani, FMK Corke, ...
GigaScience 9 (3), giaa012, 2020
Mammographic mass classification using filter response patches
Z Suhail, A Hamidinekoo, R Zwiggelaar
IET Computer Vision 12 (8), 1060-1066, 2018
Investigating the performance of generative adversarial networks for prostate tissue detection and segmentation
U Cem Birbiri, A Hamidinekoo, A Grall, P Malcolm, R Zwiggelaar
Journal of Imaging 6 (9), 83, 2020
Automated Mammogram Analysis with a Deep Learning Pipeline
A Hamidinekoo, E Denton, R Zwiggelaar
Medical Imaging with Deep Learning (MIDL), Extended Abstracts, 2019
Stain colour normalisation to improve mitosis detection on breast histology images
A Hamidinekoo, R Zwiggelaar
Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical …, 2017
A texton-based approach for the classification of benign and malignant masses in mammograms
Z Suhail, A Hamidinekoo, ERE Denton, R Zwiggelaar
Annual Conference on Medical Image Understanding and Analysis, 355-364, 2017
Artificial intelligence and digital pathology: Opportunities and implications for immuno-oncology
F Sobhani, R Robinson, A Hamidinekoo, I Roxanis, N Somaiah, Y Yuan
Biochimica et Biophysica Acta (BBA)-Reviews on Cancer, 188520, 2021
Optimal temporal resolution for decoding of visual stimuli in inferior temporal cortex
A Babolhavaeji, S Karimi, A Ghaffari, A Hamidinekoo, B Vosoughi-Vahdat
2014 21th Iranian Conference on Biomedical Engineering (ICBME), 109-112, 2014
Glioma Classification Using Multimodal Radiology and Histology Data
A Hamidinekoo, T Pieciak, M Afzali, O Akanyeti, Y Yuan
arXiv preprint arXiv:2011.05410, 2020
An AI-based method to retrieve hematoxylin and eosin breast histology images using mammograms
A Hamidinekoo, E Denton, K Honnor, R Zwiggelaar
15th International Workshop on Breast Imaging (IWBI2020) 11513, 1151319, 2020
Mammography-Histology-Linking-Model: Breast Cancer Modelling to Predict Histology Using Mammograms
A Hamidinekoo, K Honnor, E Denton, R Zwiggelaar
An Investigation Into Linking Mammographic and History Images
A Hamidinekoo
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