RETRACTED ARTICLE: Cancer detection using deep learning techniques

Breast cancer has become the most common form of in world recently having overtaken cervical urban cities. Immense research been carried out on breast and several automated machines for detection have formed, however, they are far from perfection medical assessments need more reliable services. Computer Assisted Diagnostics programs developed over past 2 decades to help radiologists interpret mammogram screening. Deep convolutional neural networks (CNN), which surpassed human output since 2012, an immense success image recognition. CNNs will revolutionize analysis images. We propose a method based Faster R-CNN, frameworks object detection. In non-human interference mammogram, device detects categorizes malignant or benign lesions. The proposed sets current status INbreast database public classification scheme, AUC = 0.95. digital mammography challenge DREAM with AUC = 0.85, mentioned here was second. When is used as sensor, accuracy data set extremely low very false positive points.