• Atisham Khan
• Silky Pareyani

Breast cancer is one of the most common cancers among women, and early detection is critical for effective treatment. Ultrasound imaging is a non-invasive and safe imaging technique that can be used to detect breast cancer in its early stages. Ultrasound images of breast tissue can provide detailed information about the internal structure of the breast, allowing for the detection of abnormalities that may indicate the presence of cancer. Convolutional Neural Networks (CNNs) are a type of deep learning algorithm that are well-suited for image recognition and classification tasks. In the context of breast cancer prediction using ultrasound images, CNNs can be used to analyze and classify images of breast tissue as either benign or malignant. This paper presents CNN deep learning technique for prediction of breast cancer using ultrasound image. Simulation is done using python spyder IDE 3.7 software.

CNN, Breast, Ultrasound Image, Classification, Machine, Deep Learning

"A CNN Deep Learning Technique for Prediction of Breast Cancer using Ultrasound Image", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 3, page no.i75-i81, March-2023, Available :http://www.jetir.org/papers/JETIR2303813.pdf

"A CNN Deep Learning Technique for Prediction of Breast Cancer using Ultrasound Image", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 3, page no. ppi75-i81, March-2023, Available at : http://www.jetir.org/papers/JETIR2303813.pdf