Bens Pardamean, Tjeng Wawan Cenggoro, Reza Rahutomo, Arif Budiarto, Ettikan Kandasamy Karuppiah
International Conference on Computer Science and Computational Intelligence 2018
Abstract: Breast cancer is one of the deadliest cancer for female nowadays. Despite of the rapid advancement in medical image analysis with the rise of deep learning, development of breast cancer detection system is limited due to relatively small size of the publicly available mammogram dataset. In this paper, we discover an eﬀective conﬁguration for transfer learning from Chest XRay pre-trained Convolutional Neural Network to overcome the small-size mammogram dataset problem. We found that the best conﬁguration achieve 90.38% validation accuracy for modiﬁed.
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