• Md Altab Uddin Molla
• Souradeep Sarkar
• Chandan Ghosh
• Nitu Saha

When using learning-based approaches, mammography image analysis, feature extraction is a critical step. Traditionally, the content of images is represented by handcrafted, problem-dependent features. Neural networks are a different strategy that has been successfully used in other fields to automatically find good features. Learning the characteristics of mammography mass tumors and then feed those features to a classification step, convolutional neural networks are evaluated in this work. The results of the research verified that this strategy is effective, in terms of the area under the ROC curve, it outperformed the most recent representation by 79.9% to 89%.

Breast cancer, Duplicate descriptors, Histogram of oriented gradients (HOG), Mammography classifiers

"A New Mass Lesion Identification Using Convolutional Neural Networks In Mammography", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 11, page no.f245-f250, November-2022, Available :http://www.jetir.org/papers/JETIR2211532.pdf

"A New Mass Lesion Identification Using Convolutional Neural Networks In Mammography", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 11, page no. ppf245-f250, November-2022, Available at : http://www.jetir.org/papers/JETIR2211532.pdf