Brain Blood Clot Detection
Built with TensorFlow, OpenCV, Python, Deep Learning
The Problem
Manual analysis of brain CT scans is time-consuming and depends on radiologist availability. An automated deep learning system can flag potential blood clots faster, serving as a second-opinion tool for medical professionals.
The Solution
A deep learning system for detecting blood clots in brain CT scans. Uses convolutional neural networks (CNNs) with TensorFlow for image classification and OpenCV for image preprocessing and segmentation. The model analyzes CT scan images to identify potential blood clot regions, aiding radiologists in faster, more accurate diagnosis. Trained on medical imaging datasets with data augmentation for improved generalization.
Key Features
CT scan analysis pipeline
CNN architecture for classification
OpenCV image segmentation
High accuracy detection
Data augmentation training
Medical imaging preprocessing
Technology Stack
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