Advancing Brain Tumor Diagnosis with AI-Powered Image Segmentation. A cutting-edge AI
solution utilizing deep learning architecture to enhance brain tumor segmentation and
classification, aiding clinicians in accurate diagnosis and treatment planning
Category: AI/ML Industry: Healthcare & Medical Imaging
Project Info
Client:
Digital Health Platform | UAE
Services:
Credit Restoration
Date:
February 12, 2024
Category:
Finance
Team:
Jonathan Hunt
Business Objective/Challenges:
Medical imaging plays a pivotal role in diagnosing and planning treatment for brain tumors, which affect millions globally. Accurate segmentation and classification of brain tumors from medical images are crucial to assist clinicians in understanding tumor characteristics.
A client required an AI-powered solution to improve brain tumor diagnosis. The main challenge was the time-consuming and complex manual process of delineating tumor boundaries and classifying different tumor types. The objective is to explore 2D Image Segmentation using neural networks for brain tumor classification and segmentation.
Automated segmentation and classification methods can significantly reduce the time required for manual analysis, improving clinical workflows and decision-making for medical professionals.
Solution/Approach
Leveraged a custom dataset combining three widely used datasets for evaluating medical image analysis methods. The dataset covers gliomas, meningiomas, and pituitary tumors and includes multi-modal MRI images with expert pixel-level annotations for tumor regions.
The neural network, with a multi-layered structure, was selected for segmentation. Hidden layers capture hierarchical features, and the output layer reconstructs a pixel-wise segmentation map. Non-linear activations and backpropagation optimize learning for accurate tumor boundary localization.
Implemented an AI-driven system that:
Accurately segments and classifies brain tumors from MRI images.
Assists clinicians in tumor delineation, quantification, and subtype identification.
Enhances diagnosis, treatment planning, and monitoring of brain tumors.
Technologies
Artificial Intelligence (AI), Machine Learning, Deep Learning, Image Processing
Images :
Business Outcome :
The AI-powered brain tumor segmentation solution significantly improves diagnostic accuracy, reducing manual effort and analysis time.
Clinicians benefit from enhanced workflow efficiency, faster tumor identification, and improved treatment planning.
Leads to better patient outcomes, increased operational efficiency in medical imaging, and scalable AI adoption in healthcare.
