Analytical Comparison of Deep Learning Algorithms for Fracture Detection

Image processing is used in a variety of applications such as image restoration, satellite imaging, and medical imaging, to name a few. Many new applications in the computer vision and image processing sectors are being developed every day thanks to the proliferation of image processing libraries, particularly OpenCV and MATLAB. The bone fracture detection method was created in MATLAB using the “Image Processing” module. The paper's goal is to use an X-ray image to classify whether or not there is a fracture. The fundamental goal of this research is to determine which Advanced Machine Learning model works best on each fracture detection dataset and provides the highest accuracy with the least amount of error. As a result, we're required to run our dataset through a variety of Machine Learning Models, compare their accuracy, and submit a report based on the findings. Different Captured X-ray Images of Different Body Parts are sent into the Software Systems that we are meant to design. The Best Model is CNN Model with Batch Wise Learning with Accuracy of 77.52% with loss function value 0.587.