A novel deep learning based framework for the detection and classification of breast cancer using transfer learning
Top Cited Papers
- 28 March 2019
- journal article
- research article
- Published by Elsevier BV in Pattern Recognition Letters
- Vol. 125, 1-6
- https://doi.org/10.1016/j.patrec.2019.03.022
Abstract
No abstract availableKeywords
Funding Information
- FCT - Fundação para a Ciência e a Tecnologia (UID/EEA/50008/2019)
- MCTIC (01250.075413/2018-04)
- Brazilian National Council for Research and Development (CNPq) (309335/2017-5)
This publication has 19 references indexed in Scilit:
- Breast cancer screening controversies: who, when, why, and how?Clinical Imaging, 2015
- Deep learningNature, 2015
- Automated Histology Analysis: Opportunities for signal processingIEEE Signal Processing Magazine, 2014
- Breast Cancer Histopathology Image Analysis: A ReviewIEEE Transactions on Biomedical Engineering, 2014
- Methods for Nuclei Detection, Segmentation, and Classification in Digital Histopathology: A Review—Current Status and Future PotentialIEEE Reviews in Biomedical Engineering, 2013
- Remote Computer-Aided Breast Cancer Detection and Diagnosis System Based on Cytological ImagesIEEE Systems Journal, 2013
- Computer-aided diagnosis of breast cancer based on fine needle biopsy microscopic imagesComputers in Biology and Medicine, 2013
- Representation Learning: A Review and New PerspectivesIEEE Transactions on Pattern Analysis and Machine Intelligence, 2013
- Classification of mitotic figures with convolutional neural networks and seeded blob featuresJournal of Pathology Informatics, 2013
- A theory of transfer learning with applications to active learningMachine Learning, 2012