Cancer is a group of diseases that may start in any body-organ such as breast; it involves abnormal cell growth and spreads to the entire body and the cancer patient may die. Mammography is a familiar method to detect breast cancer of human body. But the disadvantage of a typical mammography technique is of poor contrast; so that, micro calcifications can be overlooked by doctors while using mammograms. In this work, we propose a novel computer-assisted technique to assess mammogram images for breast cancer treatment using some commonly available tools. Our proposed methodology selects suspicious areas on images, hidden attributes are extracted from those selected areas, analyzes the extracted values, and assess the images as benign or malignant based on the extracted values. This work is used by Mammogram images from the Digital Database for Screening Mammogram (DDSM) and Mammographic Image Analysis Society (MIAS). Matrix Laboratory (MATLAB) tool is used to extract the feature values from the images. According to the experimental results, the proposed technique shows potential to accurately analyze the suspicious regions into benign and malignant. We believe that is because the suspicious regions are converted into equivalent numeric values. We plan to extend the proposed image analysis technique to study three-dimensional (3D) medical imaging.