Brain Tumor Detection Based On Convolutional Neural Network

Project Title

Brain Tumor Detection Based On Convolutional Neural Network

Project Area of Specialization Artificial IntelligenceProject Summary

This project is based on Realtime detection the user opens the camera and points towards the tumor to detect it.The second feature is a feature of pdf report where all the types of brain tumors are defined with discription.The third and final  feature scans the CNIC of the person and displays the report of respective person from cloud database.

Project Objectives

1.The aim of tumor detection is to specify the tumor location,namely active tissue or necrotic tumor tissue.

2. The primary task of preprocessing is to improve the quality of the MRI images and make it in a form suited for further processing by human or machine vision systems.

3. In addition, preprocessing helps to improve specific parameters of MRI images, such as improving the signal-to-noise ratio.

Project Implementation Method

1.CNN architecture is used as a automated feature detection to avoid manual feature detection

2. Real time object detection with mobile camera using CNN algorithm.

3. Defining type of tumor and based on type of tumor providing benefit to the patient by providing proper app features (like medicine and diet plan).

4. Detecting the level of tumor and tumor name by using fire base machine learning and also generating report at the end by using labeling.img

Benefits of the Project

 1. Diagnosis for brain tumor detection by the use of image processing and specify the tumor location.

2. Apart from several existing brain tumor segmentation and detection methology are present for MRI of brain images, our prjoect has been able to provide an accuracy of up to 80%.

3. All the steps for detecting brain tumors from MRI image acquisition preprocessing steps to successfully classification the Tumor using the segmentation technique.   

4. Detecting the level of tumor and tumor.

5. Provision of benefit to the patient by providing proper app features (like medicine and diet plan).

Technical Details of Final Deliverable

Softwares:

1). Android Institute: Using Java, Mobie app will be made.

2). Google Colab: Using python coding, algorithum will be train which can be used for detecting tumor.

3). Fire Base: Using cloud data base storage, Hybrid link will connect to Application.

4). Labeling.img: Label tumor detection of images.

5). Photoshop: import images in photoshop to make graphical content.

Final Deliverable of the Project Software SystemCore Industry TelecommunicationOther Industries IT Core Technology Artificial Intelligence(AI)Other Technologies Cloud InfrastructureSustainable 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)	70000
Android institue	Equipment	2	35000	70000