OBJECTIVE. The purpose of this article is to describe the development of digital breast
tomosynthesis (DBT) and to describe its advantages over 2D mammography for breast …

We present a deep convolutional neural network for breast cancer screening exam
classification, trained, and evaluated on over 200000 exams (over 1000000 images). Our …

Breast cancer mortality has not been reduced in Japan despite more than 20 years of
population-based screening mammography. Screening mammography might not be …

Medical images differ from natural images in significantly higher resolutions and smaller
regions of interest. Because of these differences, neural network architectures that work well …

Advances in deep learning for natural images have prompted a surge of interest in applying
similar techniques to medical images. The majority of the initial attempts focused on …

Background Computational models on the basis of deep neural networks are increasingly
used to analyze health care data. However, the efficacy of traditional computational models …

Breast cancer is the second leading cause of death in women. It occurs when cells in the
breast start to grow out of proportion and invade neighboring tissues or spread throughout …

Our study was to compare the clarity with which calcifications are seen on conventional
mammography (CM) with the same calcifications on digital breast tomosynthesis (DBT). We …

AbstractBreast malignancy is one of the primary driver of disease demise around the world.
Early diagnostics essentiallybuilds the odds of right treatment and survival, however this …

'This book gives plenty of examples of ad hominem attacks, intimidation, slander, threats of
litigation, deception, dishonesty, lies and other violations of good scientific practice. For …