Detection of Leukemia Using Deep learning Approach
2022
The project's goal is to create leukemia visuals using smart phone images of small blood smears.The convolution neural network model Res Net was used to identify leukemia imaging.In order to deliver a trustworthy diagnosis, particularly in places with fewer resources, such rural areas, the suggested project uses an in-depth study technique.This method also helps to lower the cost of diagnosis.They of far efficiency and cost of gathering photo datasets in a brief period of time, similar to microscopic blood smear images caught by the camera.Additionally, it can instantly transfer pictures of blood smears for early detection.An internet service compilesrealtimeimagesfromthehospitalaswellasmicroscopicbloodsmearimages.Intheproposedwork, the images are transferred to a convolution layer containing residual units defined by Re Lu and Batch normalization.Finally, a fully integrated layer is developed to give the predicted result of infected leukemia or virus-free images.Training to ensure accuracy and loss graphs are planned and performance metrics of the model are tested.