Open AccessClassification of Micro-Calcification in Breast from Mammographic Images using Transfer Learning
Author(s) -
Karuna Sharma*,
Saurabh Mukherjee
Publication year - 2020
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.e6945.018520
Subject(s) - transfer of learning , convolutional neural network , artificial intelligence , computer science , deep learning , categorization , mammography , breast cancer , pattern recognition (psychology) , identification (biology) , computer aided diagnosis , artificial neural network , machine learning , cancer , medicine , botany , biology
Early detection of cancer is most important for long term survival of patient. Now a days CADx are widely used for early identification of breast cancer automatically. CAD uses significant features to identify and categorize cancer. CADx based on Convolutional Neural Network are becoming popular now a days due to extracting relevant features automatically. CNNs can be trained from scratch for medical images due to various input sizes and tumor structures. But due to limited amount of medical images available for training ,we have used transfer learning approach.We developed a deep learning framework based on CNN to discriminate the breast tumor either benign or malignant using transfer learning. We used digital mammographic images containing both views from CBIS-DDSM database. We have achived training(100%) and validation accuracy greater than 90% with minimum training and validation loss. We have also compared the reaults with transfer learning using pretrained network alexnet and googlenet on same dataset.