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. Author manuscript; available in PMC: 2018 May 4.
Published in final edited form as: Comput Methods Biomech Biomed Eng Imaging Vis. 2016 Apr 28;6(3):270–276. doi: 10.1080/21681163.2016.1141063

Figure 4.

Figure 4

The original image (a) and (b) the associated ground truth. After convolution, the (c) three classes used in training can be identified. The output (d) from RADHicaL indicates that the deep learning classifiers are capable of learning the boundaries well, which forms the foundation of the computational savings.