Automatic Brain Tumor Segmentation Through Artificial Intelligence Deep Learning

Advancement in medical field with passage of time incorporating more and more technology into it with lesser need of human interaction as far as diagnoses is concern. These modern day advancements helping clinical specialists to facilitate more efficient health care systems to the patients. Biomedic

Project Title

Automatic Brain Tumor Segmentation Through Artificial Intelligence Deep Learning

Project Area of Specialization

Artificial Intelligence

Project Summary

Advancement in medical field with passage of time incorporating more and more technology into it with lesser need of human interaction as far as diagnoses is concern. These modern day advancements helping clinical specialists to facilitate more efficient health care systems to the patients. Biomedical imaging is a broad range of methods and procedures that visualize the interiors of the body in general, as well as individual organs or tissues. The key aim of the diagnostic image analysis is to improve the effectiveness of clinical assessment and proper treatment in other words to look under the skin and bone right into the internal organs. Medical image analysis allows to distinguish and explain the causes and effect of abnormalities. Recent technology upgrade in biomedical imaging uses computer vison based applications as they are providing better recognition information. Many computer vision algorithms have been widely adapted and implemented in biomedical imaging applications. Even so, biomedical computer vision is something more than just an application area. It is a broad field with an immense ability to create new techniques and architectures and can be used as a guiding factor for computer vision science. Computer vision algorithms enables us to detect and segment the abnormal parts present in the biomedical images. 

These algorithms when combined with artificial intelligence can provide us with different methods to segment or detect abnormalities present in the biomedical images automatically. Defects or abnormalities present in different organs can be analyzed with these methods. In our project we are integrating image processing techniques with artificial intelligence (AI) to segment brain tumor automatically.  We are developing a modified neural network that can show better result on a smaller custom dataset.

Project Objectives

Medical image segmentation of brain tumor is the initial step in diagnostic clinical preparation and pathological study. Tumor segmentation was and remains to be performed manually by a specialized radiologist, the procedure of manual segmentation is very time intensive. It can take hours and hours to perform the task on only one patient, and the radiologist may need to focus for a long time, which is why it is exposed to human error. Our first objective is to make an algorithm that can work efficiently for segmentation and aide radiologists for diagnosis in lesser time.

Many algorithms have been developed to do brain tumor segmentation through artificial intelligence. Segmentation of different regions on an image is one of the problems in which machine learning algorithms has found to be very successful, so we will adopt a sub branch of machine learning that is deep learning which provides better accuracy to segment tumor part from the MR images. Our objective is to make an algorithm that stands out in term of accuracy with state of the art approaches. 

Project Implementation Method

• The project implementation method starts with obtaining a dataset on which we can implement our proposed algorithm.
• After obtaining the dataset, we pre-process the dataset to make it usable with the proposed algorithm, for which we convert this dataset into an easily readable format.
• For making the training dataset we apply image processing techniques on the images. This process produce ground truth images that will be used in training part of the neural network.
• The next step is to develop a neural network that can segment the brain tumor automatically.

Benefits of the Project

• The project will benefit the radiologists in making a fast diagnosis.
• It will automate the process of segmentation.
• In a country like Pakistan which is still developing, the project can aid the radiologists in their examination of disease.
• The project can be further modified in the future according to specific needs.

Technical Details of Final Deliverable

Final deliverables will be in the form automated segmented image. This image will be the predicted output of the proposed neural network.

Final Deliverable of the Project

Software System

Core Industry

IT

Other Industries

Medical , Health

Core Technology

Artificial Intelligence(AI)

Other Technologies

Others

Sustainable Development Goals

Industry, Innovation and Infrastructure

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com