Ischemic and hemorrhage stroke prediction using DL algorithm

Project Code :TCMAPY421


The objective of this project is about detection of brain stroke disease, this study attempts to perform early detection on brain stroke images. Our model will help to detect the stroke is positive or negative which reduce the burden to the people who are continuously working on this domain.


For the last few decades, machine learning is used to analyze medical dataset. Recently, deep learning technology gaining success in many domains including computer vision, image recognition, natural language processing and especially in medical field of radiology. This project attempts to diagnose brain stroke from CT using CNN and deep learning models. The proposed methodology is to classify brain stroke CT images into normal and abnormal images. In particular, three types of convolutional neural network that are ResNet, MobileNet and VGG16 are used. For classification, we passed pre-processed stroke CT for training, trained all layers and classify normal and abnormal patient. Then this abnormal patient data stored into two-dimensional array and passed this to get result. The experimental result show that classification model achieves best accuracy. Through experimental results, we found that deep learning models not only used in non-medical images but also give accurate result on medical image diagnosis, especially in brain stroke detection.

 Keywords: Brain stroke, deep learning, convolutional neural network.

NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.

Block Diagram



  • Processor: I3/Intel
  • Processor RAM: 4GB (min)
  • Hard Disk: 128 GB
  • Key Board: Standard Windows Keyboard
  • Mouse: Two or Three Button Mouse
  • Monitor: Any


  • Operating System: Windows 7+
  • Server-side Script: Python 3.6+
  • IDE: PyCharm
  • Libraries Used: Pandas, Numpy,Flask.

Learning Outcomes

  •          Practical exposure to
    •     Hardware and software tools
    •     Solution providing for real time problems
    •     Working with team/individual
    •     Work on creative ideas
  •          Testing techniques
  •          Error correction mechanisms
  •          What type of technology versions is used?
  •          Working of Tensor Flow
  •          Implementation of Deep Learning techniques
  •          Working of CNN algorithm
  •          Working of GoogleNet algorithm
  •          Working on ResNet50
  •          Working on VGG16 and VGG19
  •          Working on AlexNet
  •          Working of Transfer Learning
  •          Building of model creations
  •          Scope of project
  •          Applications of the project
  •          About Python language
  •          About Deep Learning Frameworks
  •          Use of Data Science

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