Skin Cancer Classification

Project Title

Skin Cancer Classification

Project Area of Specialization Computer ScienceProject Summary

Since the last decade, Cancer has been a severe disease that people are afraid of. Of all the types of Cancer, Skin cancer has been the most serious among the types of cancer, because our human body has the largest organ that is skin. The American Academy of Dermatology Association states that, in the U.S., more than 9,500 people are diagnosed with skin cancer every day. More than two people die of the disease every hour. More than 5.4 million cases of nonmelanoma skin cancer were treated in over 3.3 million people in the U.S. Skin Cancer being such severe disease requires rapid identification of disease. If not so, then it would be considered just acne or pimple. That’s why using latest trends of Artificial Intelligence e.g., Deep Learning, Image Processing etc. would provide rapid classification result of Skin Cancer unlike traditional methods and by using those trends the overall cost of tests for identification of Skin Cancer can be reduced. This project is about providing a model that is able to detect skin cancer. For the training purpose of this project, deep learning and image processing latest techniques would be used so as to increase the precision and accuracy of model which is the main challenge. I would be applying different algorithms of artificial intelligence through which this trained model will be able to provide specific accuracy of the tested images. Subsequently, this project will be deployed as a web based application that would be provide accessibility to the user and ultimately rapid results within the reach of few seconds. This project would open the doors of the latest computing technologies to be used for the field of medical sciences for further research purposes.

Project Objectives

• Accessibility: A common person can have access of application using which he can classify Skin Cancer
• Time Saving: Time can be saved due to autonomous application of classification of Skin Cancer
• Rapid Results: The proposed idea can provide rapid solutions to the end user as compared to traditional methods
• Multiple Choice of Models: While training, various datasets would be used
• Deliverable: Provide Web Application as a Deliverable at the end and that can also save images

Project Implementation Method

The project implementation includes:

1. Find out the best algorithms and classification models that works well for image classification
2. Find out different Skin Cancer Datasets available
3. Training best available models on my datasets
4. Retraining the models on different dataset
5. Testing model after training
6. Deploying model
7. Testing models on real-world data
8. Analysis of data based on obtained result

Benefits of the Project

• This project would be developed by being trained on different dataset
• This project would allow end users to choose different model for classification
• This project would allow user to save the images in their account and load those images

Technical Details of Final Deliverable

• Hardware Interfaces
  • None
• Software Interfaces
  • SQLite Database: SQLite database will be used to store the data of users, because it is lite weight
  • Django Framework: To provide web based application
  • Django File Handling: To store images
  • Pytorch: This would be used to support the development, training of model, and testing of deep learning models.
• Communications Interfaces
  • This web based application can be accessed using browsers from one’s device

Final Deliverable of the Project HW/SW integrated systemCore Industry MedicalOther Industries Education , IT , Others , Health Core Technology Artificial Intelligence(AI)Other TechnologiesSustainable Development Goals Good Health and Well-Being for PeopleRequired Resources

Item Name	Type	No. of Units	Per Unit Cost (in Rs)	Total (in Rs)
			Total in (Rs)	80000
ZOTAC GeForce RTX 2080 AMP 8GB	Equipment	1	70000	70000
Domain Expense for Website	Miscellaneous	1	10000	10000