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Smart Buddy: Detection and Classification of Breast Cancer Abnormalities

Supervised By:
Imran Ihsan
Duration:
2019 - 2020
Client:
Team:
Completed:
Project completed in 100%.
System Architecture Diagram
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Project description

Detection and Classification of Breast Cancer Abnormalities through Convolutional Neural Networks and Inception V3

Breast cancer is among world’s second most occur-ring cancer in all types of cancer. Most common cancer among women worldwide is breast cancer. There is always need of advancement when it comes to medical imaging. Early detection of cancer followed by the proper treatment can reduce the risk of deaths. Machine learning can help medical professionals to diagnose the disease with more accuracy. Where deep learning or neural networks is one of the techniques which can be used for the classification of normal and abnormal breast detection. Deep learning is a machine learning technique in which a computer model performs classification tasks directly learning from text, images or sound. Models are trained on a large number of datasets and CNN architectures containing many layers. In medical imaging deep learning is used to detect cancer cells automatically. Training a deep convolution network from start is difficult because it needs large amount of data for training. CNN can be used for t

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