Real Time Skin Cancer Detection App using Transfer Learning

Skin cancer is one of the most world-wide diseases that cause death. It is the abnormal growth of skin cells, most often develops on skin exposed to the sun. But this common form of cancer can also occur on areas of your skin not ordinarily exposed to sunlight. There are three major types

Project Title

Real Time Skin Cancer Detection App using Transfer Learning

Project Area of Specialization

Artificial Intelligence

Project Summary

Skin cancer is one of the most world-wide diseases that
cause death. It is the abnormal growth of skin cells, most often develops on skin exposed to the sun. But this common form of cancer can also occur on areas of your skin not ordinarily exposed to sunlight.

There are three major types of skin cancer

• Basal cell carcinoma
• Squamous cell carcinoma
• Melanoma

Note: two types of carcinoma are very near to each other so usually initial categorization comes in melanoma and non-melanoma.

Early detection of these lesions may increase the curing rate to 90%. The high similarity
between different types of skin lesions makes the visual examination hard and may lead to wrong investigation. Therefore, an automated system is required for skin lesion classification.

Skin cancer is the cancer you can see. Unlike cancers that develop inside the body, skin cancers form on the outside and are usually visible. That’s why skin exams, both at home and with a dermatologist, are especially vital. Early detection saves lives. This project gives the power to detect cancer early when it’s easiest to cure, before it can become dangerous, disfiguring or deadly.

Melanoma is the deadly cancer type that even take the lives of the people immediately. The early detection of melanoma is very important to save the lives of the peole. Therefore, in this project we will develop an android app that will detect the melanoma skin cancer on real-time and can save the lives of the patients. 

Project Objectives

The objective of this project is to develop a smart android app that is intelligent to detect skin cancer on real-time scenerio. 

The output of this project will

• The primary objective of this Project is to develop a framework that is capable of analyzing Melanoma Skin Cancer.
• The second objective is to measure or evaluate the risk of melanoma using Skin lesion images or dermatological images.
• Finally, to detect and classify the Melanoma or Benign (Non- Melanoma).
• To reduce the gap between the dermotologists and skin cancer patients.
• To save the lives of the patients having melanoma at very early stages using this app.
• Detection and Analysis of Skin Cancer
• Binary classification of Melanoma and Non-Melanoma skin cancers

Project Implementation Method

We have used 6 transfer learning models in our project.

1. MobileNetV2

2.VGG16

3.InceptionV3

4.MobileNetV2 with Fine tuning 

5. VGG16 with Fine tuning 

6.InceptionV3 with Fine tuning 

Our MobileNetV2 with finetuning models gives us 99.99% accuracy on melanoma detection as compared to other models. 

We have used MobileNetV2 model to make our android app because it is a light weighted and more efficient model for mobile app development. 

Benefits of the Project

The benefit of the Skin Cancer Detection App is to detect the pre-cancerous symptoms at an initial stage. The idea of this project is to help prevent the skin cancer or to avoid fatal complications. The advantage is to improve the condition at the very initial stage.

From this project, the people will use this easy-to-use android app that can save thier lives which is one of the most important benefit of our project. 

The Application can avoid severe complications and improves the health of the person. In this way, it will impact people positively. 

Technical Details of Final Deliverable

Final Deliverable:

Software Application (Android app)

Documentations

Reports

Proposals

Gantt Charts and Log books

Research Paper (Published)

Front-end development

Back-end development

Models building

Models Live testing

User Interface 

Live training and testing

Model integration in android app 

Result testing and validation

Final Deliverable of the Project

Software System

Core Industry

Health

Other Industries

IT , Medical

Core Technology

Artificial Intelligence(AI)

Other Technologies

Others

Sustainable Development Goals

Good Health and Well-Being for People

Required Resources

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