Conventional Machine Learning and Deep Learning Approach for Multi-Classification of Breast Cancer Histopathology Images—a Comparative Insight
Published 2020 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Conventional Machine Learning and Deep Learning Approach for Multi-Classification of Breast Cancer Histopathology Images—a Comparative Insight
Authors
Keywords
-
Journal
JOURNAL OF DIGITAL IMAGING
Volume -, Issue -, Pages -
Publisher
Springer Science and Business Media LLC
Online
2020-01-04
DOI
10.1007/s10278-019-00307-y
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Hello World Deep Learning in Medical Imaging
- (2018) Paras Lakhani et al. JOURNAL OF DIGITAL IMAGING
- Access to pathology and laboratory medicine services: a crucial gap
- (2018) Michael L Wilson et al. LANCET
- Histopathological Breast Cancer Image Classification by Deep Neural Network Techniques Guided by Local Clustering
- (2018) Abdullah-Al Nahid et al. Biomed Research International
- Classification of Breast Cancer Based on Histology Images Using Convolutional Neural Networks
- (2018) Dalal Bardou et al. IEEE Access
- Classification of breast cancer histology images using Convolutional Neural Networks
- (2017) Teresa Araújo et al. PLoS One
- Breast Cancer Multi-classification from Histopathological Images with Structured Deep Learning Model
- (2017) Zhongyi Han et al. Scientific Reports
- Automatic Classification of Cancerous Tissue in Laserendomicroscopy Images of the Oral Cavity using Deep Learning
- (2017) Marc Aubreville et al. Scientific Reports
- A Dataset for Breast Cancer Histopathological Image Classification
- (2016) Fabio A. Spanhol et al. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
- Automatic prediction of tumour malignancy in breast cancer with fractal dimension
- (2016) Alan Chan et al. Royal Society Open Science
- US precision-medicine proposal sparks questions
- (2015) Sara Reardon NATURE
- Deep learning
- (2015) Yann LeCun et al. NATURE
- A New Initiative on Precision Medicine
- (2015) Francis S. Collins et al. NEW ENGLAND JOURNAL OF MEDICINE
- Breast Cancer Histopathology Image Analysis: A Review
- (2014) Mitko Veta et al. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
- Computer-aided detection of breast cancer on mammograms: A swarm intelligence optimized wavelet neural network approach
- (2014) J. Dheeba et al. JOURNAL OF BIOMEDICAL INFORMATICS
- One-class kernel subspace ensemble for medical image classification
- (2014) Yungang Zhang et al. EURASIP Journal on Advances in Signal Processing
- Pathologist Workforce in the United States: I. Development of a Predictive Model to Examine Factors Influencing Supply
- (2013) Stanley J. Robboy et al. ARCHIVES OF PATHOLOGY & LABORATORY MEDICINE
- Image Classification of Human Carcinoma Cells Using Complex Wavelet-Based Covariance Descriptors
- (2013) Furkan Keskin et al. PLoS One
- Orthogonal Rotation-Invariant Moments for Digital Image Processing
- (2008) Huibao Lin et al. IEEE TRANSACTIONS ON IMAGE PROCESSING
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExploreDiscover Peeref hubs
Discuss science. Find collaborators. Network.
Join a conversation