The topological derivative (TD) for shape analysis has been employed
in image segmentation, and machine learning schemes based on
convolutional neural network (CNN) provide the high performance in
the image processing. The supervised and unsupervised approaches
have different roles and advantages according to their concepts. To
maximize the benefits of two approaches, we propose CNN-TD based
segmentation approach. A CNN-based segmentation scheme is employed
to faithfully consider the characteristics of an object to be
segmented in a given image, and we refine the CNN results using a
TD-based scheme. Experimental results show that the proposed scheme
produces better performance for the prostate segmentation than the
refined results by level set-based schemes. Therefore, we believe
that the proposed scheme can be a useful tool for effective medical
image segmentation.