prakharrathore123 / brain-tumor-detection

Brain Tumor is one the most deadly disease whose detection and treatment is one of the toughest tasks. At present, treatment of patients requires clinical pictures examination and is becoming a critical field. It fuses a wide scope of imaging procedures some of them are Computed Tomography channels (CT examines), Magnetic Resonance Imaging (MRIs) and X-columns and so forth. Medical experts perform tumor segmentation on data obtained from magnetic resonance imaging (MRI) which is very time consuming. Brain tumor segmentation is a significant process to extract information from complex MRI of brain image. Segmentation assessment is done by human, which can involve human errors in the result. So we have choose this topic because it is one of the most difficult and trending arena whose precision is the most important thing than any think else. So we implemented the detection using 2 ways the first one is the OpenCV method done using python. It takes MRI image as input and performs basic pre-processing. We have also implemented another process using or a way without using any big standard library and using convolution and integrated with machine leaning this predicts, the presence of the tumor region in the brain. This 2 method help us to detect the basic region where the tumor is present and highlights the region where the tumor is present. So this in a good way and highly précised way for the detection of the tumor in the MRI images of the brain. Doing it technically reduces the chance of error in a very great manner.

Brain-Tumor-Detection

Image Processing J component MODEL-1 USING OPEN CV Step 1: Open pycharm, google colab, jupiter notebook. Step 2: Using the code replace the name of the image you want to check for the which has tumor in it or not. Step 3: Save the image in the directory and then replace the name in the code. Step 4: Then run the code. Step 5: We can observe several outputs which shows us the transition the image is going through or processes involved. Step 6: The final image if it contains red circle surrounding a particular area then it has tumor in it or else no tumor.

MODEL-2 USING ML WITH CONVULATION Step 1: Open google colab. Step 2: Upload the images in google drive. Step 3: Import the yes images of dataset. Step 4: Import the no images of the dataset from drive to colab. Step 5: Let the partitions of code run you can see the transition outputs in the middle. Step 6: The last part in prediction change the input image and check for the result. Step 7: U will get tumor is present or not.