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ages needs further improvement. After optimizing the
hyper-parameters of our simulation we will be able
to form a paired dataset (CT-Ultrasound pairs) which
can be used for training a generative adversarial net-
work GAN in a supervised manner and finally testing
it on reconstructing the CT images from the real US
images. The potential utility of this work is to train
deep neural networks for the inverse problem of sim-
ulating CT images from the given US images, which
can aid clinicians in diagnosis and surgical interven-
tion.
ACKNOWLEDGEMENT
This work would not have been possible without the
financial support of the Qualcomm Innovation Fel-
lowship Award, India. We are indebted to the devel-
oper of Stride, Mr. Carlos Cueto from Imperial Col-
lege London, for his feedback and support.
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