Abstract

Deep learning has recently developed as quickly rising field for the analysis of different medical images. Ultrasound (US) has developed as one of the most frequently clinically used imaging modalities. Although, it is a quickly developing technology but it also has challenges like low imaging quality and high variability. So, it is desirable to progressively develop techniques for automatic analysis of US images for diagnosis. Now a days, Deep learning is also widely used technique for analysis of many US images. In this review, we surveyed different deep learning techniques used for classification, detection, and segmentation along with the challenges of deep learning in US image analysis.

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