Breast Cancer Detection & Classification using Transfer Learning

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Project Title

Breast Cancer Detection & Classification using Transfer Learning

Project Area of Specialization

Artificial Intelligence

Project Summary

• Breast Cancer is the most common disease among women all over the world.
• 6,90,000 cases have been reported in Pakistan between 2017 – 2018.
• Traditional Process is Long and Expensive. Because of these factors, there's also a lack of follow-up on Patients.
• Machine Learning aided detection and classification can help the Radiologists filter out the Digital Mammograms of the patients preemptively.
• And it can also serve as a double-check for the Radiologist so that no diagnosis is made inaccurately. 

Project Objectives

• To precisely detect Breast Cancer in Digital Mammograms (if any)
• To accurately classify cancerous tissues & effected masses as Benign or Malignant.
• To accurately generate computable features for further analysis of the Digital Mammograms.

Project Implementation Method

• We intend to use Transfer Learning, a machine learning technique, to detect and classify breast cancer in digital mammograms.
• As ML can be very resource intensive, we intend to train our models in the cloud.
• We also want to build our final application based on the cloud infrastructure, so that medical experts can use it from anywhere, anytime without requiring any specs-heavy hardware systems.
• Server-side implementation of the back-end and ML engine can enable us to gather Digital Mammography and Breast Cancer data from many medical experts from different areas to retrain and better our models and have a better statistical understanding of the problem in Pakistan.

Benefits of the Project

• Building a Precise Breast Cancer Detector
• Generation of a Meaningful Visual Vocabulary for Breast Cancer Classification
• Robust Multi - Class Classifier for Classification of Malicious Tissues
• ML aided Classification for Breast Cancer, Averse to Over-fitting

Technical Details of Final Deliverable

• Bag of Features is intended to be used for Feature Generation and Categorization of Digital Mammograms.
• Support Vector Machines are intended to be used for the Detection and Classification of Breast Cancer in Digital Mammograms.
• The final application is intended to be deployed in the cloud to remove any specs-intensive hardware requirements by the medical professionals (the intended user) and their ease of access.

Final Deliverable of the Project

Software System

Type of Industry

Medical , Health

Technologies

Artificial Intelligence(AI), Cloud Infrastructure, Big Data

Sustainable Development Goals

Good Health and Well-Being for People

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com