BONE FRACTURE DETECTION SYSTEM – Project Topics for Student
In this paper, we proposed automated techniques and methods for detecting fracture. Manual examination of X-ray images is time-consuming and error-prone. Because X-ray images are more prone to noise, we used a number of preprocessing steps to remove noise and blur from the image. As a result, the system can detect fractures more precisely. The system detects fractures based on their type.
Noise is removed from the image, and the image is transformed to make it clearer so that the system can detect fractures more easily. To track bone, we used image processing methodology. The system removes all unwanted as well as smaller objects.
Finally, the system detects fracture based on the connected component. The system shows a bounding box around the fracture. This system includes image preprocessing steps as well as fracture detection based on fracture type. The proposed system can detect bone dislocation with an 80% success rate, major fractures with a 60%-70% accuracy, and minor fractures with a 50%-60% accuracy.
Advantages
Image processing is used efficiently.
Fracture Detection that is Automated.
This system will make orthopedics easier.
Disadvantages
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BONE FRACTURE DETECTION SYSTEM – Project Topics for Student
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