Abstract
View planning is the process of prescribing slices for diagnostic imaging. It is an important part of the magnetic resonance imaging (MRI) investigation workflow affecting both speed and quality of diagnoses made by physicians. In this chapter, we present a framework for automatic view planning (AVP) consisting of a universal, deep multi-layer discriminative architecture for landmark detection and several pre-processing and post-processing algorithms designed for different kinds of MRI data. The framework is applicable to a wide variety of MRI procedures such as brain, cardiac, knee and spine MRI. The AVP framework and performance of underlying algorithms were calculated on real clinical MRI data and implemented as a product-ready solution. Evaluation results show superior quality and speed over competitors.
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