Automated Breast Cancer detection with Mammograms:
Built a CAD system to preprocess mammograms and extract texture features from it. Computer Vision library (OpenCV) was used to analyze the images and GLCM (Gray-level Co-Cooccurrence matrix) for feature extraction after apply different filters including Roberts for texture detection, which then transformed into Pandas DataFrame. Mini-DDSM database was used. Trained statistical and neural network models for further prediction. Logistic regression was used as statistical model with proper hyperparameter tuning. The front-end (Desktop Application) was designed using Figma and Tkinter i.e. python library for developing GUI.
