  The continuity of biological tissue between consecutive biomedical images
makes it possible for the video interpolation algorithm, to recover large area
defects and tears that are common in biomedical images. However, noise and blur
differences, large deformation, and drift between biomedical images, make the
task challenging. To address the problem, this paper introduces a
deformation-aware network to synthesize each pixel in accordance with the
continuity of biological tissue. First, we develop a deformation-aware layer
for consecutive biomedical images interpolation that implicitly adopting global
perceptual deformation. Second, we present an adaptive style-balance loss to
take the style differences of consecutive biomedical images such as blur and
noise into consideration. Guided by the deformation-aware module, we synthesize
each pixel from a global domain adaptively which further improves the
performance of pixel synthesis. Quantitative and qualitative experiments on the
benchmark dataset show that the proposed method is superior to the
state-of-the-art approaches.
