Efficient Brain Tumor Segmentation with Multiscale  Two-Pathway-Group Conventional Neural Networks

Efficient Brain Tumor Segmentation with Multiscale Two-Pathway-Group Conventional Neural Networks

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Product Code: Python - Deep Learning
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Product Description

Aim:

          To detected the Brain Tumor using Two-Pathway-Group Conventional Neural Networks.


Synopsis:

          Brain tumor identification is really challenging task in early stages of life. But now it became advanced with deep-learning. Now a day’s issue of brain tumor automatic identification is of great interest. In Order to detect the brain tumor of a patient we consider the data of patients like MRI images of a patient’s brain. Here our problem is to identify whether tumor is present in patients brain or not. It is very important to detect the tumors at starting level for a healthy life of a patient. There are many literatures on detecting these kinds of brain tumors and improving the detection accuracies. In this paper, we estimate the brain tumor severity using Convolutional Neural Network algorithm which gives us accurate results.
         

Proposed System


          We are providing new methods of MRI images of Brain of a patient.  Here pre-processing is done by Gaussian which is a linear filter.  Then feature Extraction is done for the images by GLCM features. Finally classification applied through an algorithm Convolutional neural networks which will identify the tumor regions

 

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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
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  10. Reference Papers
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  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.