Computer Aided Mass Detection in Mammograms
Gunturu Krishna Chaitanya, Vivek Kukkapalli, I S K Vishwanath Varma, S K. Md. Hussain Basha, Devi Vijayan · 2021
Radiologist's expertise in identifying and sleuthing breast cancer can be helped by utilizing some modernized feature extraction and classification techniques. In the proposed Computer Aided Diagnosis (CAD) framework, different techniques have been utilized. Pre-processing of mammograms is performed to stifle the noise present in the mammograms. The images are classified as low dense and high dense. Feature extraction is carried out to recognize the significant and vital parts from the image utilizing the techniques namely Local Phase Quantization (LPQ), Local Binary Pattern (LBP), and Gray- Level Co-Occurrence Matrix (GLCM) for both high dense and low dense images. Experiments were done using the 2749 images from the DDSM dataset. The outcomes exhibited the adequacy of the proposed framework and show the imperativeness for clinical applications.