DermGAN: Synthetic Generation of Clinical Skin Images with Pathology

20 Nov 2019 • Amirata Ghorbani • Vivek Natarajan • David Coz • Yu-An Liu

Despite the recent success in applying supervised deep learning to medical imaging tasks, the problem of obtaining large and diverse expert-annotated datasets required for the development of high performant models remains particularly challenging. In this work, we explore the possibility of using Generative Adverserial Networks (GAN) to synthesize clinical images with skin condition... (read more)

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METHOD	TYPE
Concatenated Skip Connection	Skip Connections
PatchGAN	Discriminators
ReLU	Activation Functions
Batch Normalization	Normalization
Leaky ReLU	Activation Functions
Sigmoid Activation	Activation Functions
Dropout	Regularization
Pix2Pix	Generative Models
Convolution	Convolutions
GAN	Generative Models

METHOD

TYPE

Concatenated Skip Connection