1 |
Abhishek Vahadane, Tingling Peng, Amit Sethi, Shadi Albarqouni, Lichao Wang, Maximilian Baust, et al., Structure-Preserving Color Normalization and Sparse Stain Separation for Histological Images, IEEE TRANSACTIONS ON MEDICAL IMAGING, (2016)
|
2 |
Peter Byfield, StainTools, Retrieved from https://staintools.readthedocs.io/en/latest/, (2018)
|
3 |
Breast Cancer - WHO. World Health Organization, (2021)
|
4 |
American Cancer Society. Surveillance Research, (2019)
|
5 |
Ismail Jatoi, The Natural History of Breast Cancer. Surgical Clinics of North America, Science Direct, (2005)
|
6 |
Asmaa Ibrahima, Paul Gamble, Ronnachai Jaroensri, Mohammed M.Abdelsamea, Craig H.Mermel, Po-Hsuan Cameron Chen, et al, Artificial intelligence in digital breast pathology: Techniques and applications, The Breast, SceinceDirect, (2019)
|
7 |
Sandhya Armoogum Ph.D., Xiaoming Li Ph.D., Training Datasets, Retrieved from https://www.sciencedirect.com/topics/computer-science/training-datasets, (2019)
|
8 |
Xinyue Wang, Bo Liu, Siyu Cao, Liping Jing & Jian Yu, Important sampling-based active learning for imbalanced classification, SpringerLink, (2020)
|
9 |
Neofytos Dimitriou, Ognjen Arandjelovic and Peter D. Caie, Deep Learning for Whole Slide Image Analysis: An Overview, frontiers in Medicine, (2019)
|
10 |
Juanying Xie, Ran Liu, Joseph Luttrell IV and Chaoyang Zhang, Deep Learning Based Analysis of Histopathological Images of Breast Cancer, frontiers in Genetics, (2019)
|
11 |
Shallu, Rajesh Mehra, Breast cancer histology images classification: Training from scratch or transfer learning? ICT Express, (2018)
|
12 |
Kaushiki Roy, Debapriya Banik, Debotosh Bhattacharjee, Mita Nasipuri, Patch-based system for Classification of Breast Histology images using deep learning, Computerized Medical Imaging, and Graphics, (2019)
|
13 |
BACH ICIAR 2018 Grand Challenge on Breast Cancer Histology, Retrieved from https://iciar2018-challenge.grand-challenge.org/, (2018)
|
14 |
Deron Eriksson, Fei Hu, Whole-slide image preprocessing in Python, IBM, (2018)
|
15 |
Rebecca Stone, Introducing py_wsi for computer analysis on whole slide .svs images using OpenSlide, (2018)
|
16 |
Mingyu Gao, Dawei Qi, Hongbo Mu and Jianfeng Chen, A Transfer Residual Neural Network Based on ResNet-34, forests, MDPI, (2019)
|
17 |
Valentina Alto, Neural Networks: parameters, hyperparameters, and optimization strategies, Retrieved from https://towardsdatascience.com/neural-networks-parameters-hyperparameters-and-optimization-strategies-3f0842fac0a5, (2019)
|
18 |
Jason Brownlee, Random Oversampling and Undersampling for Imbalanced Classification Retrieved from https://machinelearningmastery.com/random-oversampling-and-undersampling-for-imbalanced-classification/. (2020)
|
19 |
Agrawal, Astha; Herna L. Viktor, Eric Paquet, SCUT: Multi-class imbalanced data classification using SMOTE and cluster-based undersampling, IEEE Xplore, (2015)
|
20 |
Alexander Rakhlin, Alexey Shvets, Vladimir Iglovikov, and Alexandr A. Kalinin, Deep Convolutional Neural Networks for Breast, arXiv, (2018)
|