Brain Tumor Detection and Classification Using Convolutional Neural Network (CNN)

Brain Tumor Detection and Classification Using Convolutional Neural Network (CNN)

₹5,500.00 ₹4,000.00
Product Code: Python - Deep Learning
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Product Description

Aim:

               To detect and identify the Brain Tumor using Deep-Learning techniques.

Abstract:

               Medical image processing is that the one among the foremost demanding and promising field nowadays. Tumor is a rapid uncontrolled growth of cell. The tumor are often classified as benign, malignant and premalignant. When a tumor is noticed as malignant then the tumor results in cancer. Earlier stage of tumor is used to be detected manually through observation of image by doctors and it takes more time and sometimes gets inaccurate results. Today different computer added tool is employed in medical field. These tools provide a quick and accurate result. Magnetic Resonance Images (MRI) is the most widely used imaging technique for analyzing internal structure of human body. The MRI is used even in diagnosis of most severe disease of medical science like brain tumors. The brain tumor detection process consist of image processing techniques involves four stages. Image pre-processing, image segmentation, feature extraction, and finally classification.

Proposed System

             Automated brain tumour detection is extremely necessary as high accuracy is required when human life is involved. Automated detection of tumor in MR images involves feature extraction and classification using machine learning algorithm. Our approach consists of three steps: (A) Brain image pre-processing, (B) Brain feature extraction, (C) brain tumour classification using web application. The input of the approach is that the brain images and therefore the output are the respective sort of the brain tumour.


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Package Includes

Software Projects Includes

  1. Demo  Video
  2. Abstract
  3. Base paper
  4. Full Project PPT
  5. UML Diagrams
  6. SRS
  7. Source Code
  8. Screen Shots
  9. Software Links
  10. Reference Papers
  11. Full Project Documentation
  12. Online support


The Delivery time for software projects is 2 -3 working days. Some of the software projects will require Hardware interface. Please go through the hardware Requirements in the abstract carefully. The Hardware will take 7-8 Working Days

 

Hardware Projects Includes

  1. Demo  Video
  2. Abstract
  3. Base paper
  4. Full Project PPT
  5. Datasheets
  6. Circuit Diagrams
  7. Source Code
  8. Screen Shots & Photos
  9. Software Links
  10. Reference Papers
  11. Lit survey
  12. Full Project Documentation
  13. Online support


The Delivery time for Hardware projects is 7-8 working days.

   

Mini Projects: Software Includes

  1. Demo  Video
  2. Abstract
  3. Base paper
  4. Full Project PPT
  5. UML Diagrams
  6. SRS
  7. Source Code
  8. Screen Shots
  9. Software Links
  10. Reference Papers
  11. Full Project Documentation
  12. Online support

 

The Delivery time for software Miniprojects is 2 -3 working days.

 

Mini Projects - Hardware includes

  1. Demo  Video
  2. Abstract
  3. PPT
  4. Datasheets
  5. Circuit Diagrams
  6. Source Code
  7. Screen Shots & Photos
  8. Software Links
  9. Reference Papers
  10. Full Project Documentation
  11. Online support

The Delivery time for Hardware Mini projects is 7-8 working days.