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Detection of Brain Tumor Classification

Detection of Brain Tumor

Price : 10000

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Course Duration
Approx 10

Course Price
₹ 10000

Course Level
High

Course Content

Abstract

A brain tumor is a growth of abnormal cells that has formed in the brain. Some brain tumors are cancerous (malignant), while others are not (non-malignant). A brain tumor is an abnormal growth of cells inside the brain or skull. Primary tumor : grows from the brain tissue. Secondary tumor : cancer cells from different part of the body spreads to the brain. Most Research in developed countries show that the number of people who have brain tumors were died due to the fact of inaccurate detection. Generally, CT scan or MRI that is directed into intracranial cavity produces a complete image of brain. This image is visually examined by the physician for detection & diagnosis of brain tumor. However this method of detection resists the accurate determination of type & size of tumor.  In recent times, the introduction of information technology and e-health care system in the medical field helps clinical experts to provide better health care to the patient. This study addresses the problems of segmentation of abnormal brain tissues and normal tissues such as gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) from magnetic resonance (MR) images. We proposed a system that detects the brain tumor with help of deep learning neural networks.

INTRODUCTION

A neurological exam is usually the first step for figuring out the cause for symptoms. The goal is to see how well the nervous system is working. A brain scan is a type of diagnostic test that takes pictures of the brain. Like an X-ray can see inside the body to diagnose a broken bone, a brain scan can see inside the skull to see a brain tumor. The two most common scans for diagnosing a brain tumor are magnetic resonance imaging (MRI) and computed tomography (known as a CT or CAT scan). In recent years, biomarkers have been used to identify certain tumors. Biomarkers are other distinct cellular materials, such as proteins or DNA from brain tumor cells. These biomarkers can be collected in the blood, urine, cerebral spinal fluid, saliva, or brain tissue. These tiny bits of genetic material are being explored for their potential use in the diagnosis, treatment, and monitoring of the effectiveness of medications in patients with brain tumors. Deep learning techniques are gaining popularity in many areas of medical image analysis, such as computer-aided detection of breast lesions, computer-aided diagnosis of breast lesions and pulmonary nodule, and in histopathological diagnosis. There are several types of deep learning approaches that have been developed for different purposes, such as object detection and segmentation in images, speech recognition, and genotype/phenotype detection and classification of diseases. Some of the known deep learning algorithms are stacked auto-encoders, deep Boltzmann machines, deep neural networks, and convolutional neural networks (CNNs). CNNs are the most commonly applied to image segmentation and classification We proposed a system that detects the brain tumor with help of deep learning neural networks and other related libraries like keras, tensorflow and opencv.

 

BLOCK DIAGRAM

BLOCK DIAGRAM

2.3       Project requirements

A. Hardware Requirement

Ø System         :        Pentium IV 2.4 GHz.

Ø Hard Disk    :        500 GB.

Ø Ram            :        4 GB

Ø Any desktop / Laptop system with above configuration or higher level

Ø

B. Software Requirements

Ø Operating system            :         Windows XP / 7

Ø Coding Language           :         Python

Ø Interpreter                      :         Python IDE

Ø Packages                        :        Opencv,  Keras, Tensorflow

 

 

C. Functional Requirements:-

·        Detect brain tumor accurately with the help of deep learning techniques.

D. Non Functional Requirements:-

They basically deal with issues like:

      Security

      Maintainability

      Reliability

      Scalability

      Performance

Conclusion

 

A brain tumor is a growth of abnormal cells that has formed in the brain. Some brain tumors are cancerous (malignant), while others are not (non-malignant). The existing methods for detection & diagnosis of brain tumor not  accurate determine the type and size of tumor. We proposed a system that detects and classify the brain tumor with help of deep learning neural networks and other related libraries like keras, tensorflow and opencv.

 

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