Researchers have succeeded in developing a new model called ECGMLP to automatically diagnose endometrial cancer through histopathological analysis. This model, based on advanced multilayer neural network, has been able to perform better performance than previous methods.
Key image processing steps in this model include:
1. Preparation of images with normalization techniques, noise removal and contrast improvement
2. Careful classification of images by combining Atasu’s threshold, morphological operations and cascade algorithm
1. Extraction of relevant features and removing unrelated patterns
1. Final classification of images with processing block architecture
Benefits of this new method:
Reduction of diagnosis error compared to conventional methods
The possibility of integrating with current medical diagnosis systems
Potential of use to diagnose early and improve therapeutic results
Reduce costs and time of diagnosis
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