Brain Lesion Synthesis via Progressive Adversarial Variational Auto-Encoder

by   Jiayu Huo, et al.

Laser interstitial thermal therapy (LITT) is a novel minimally invasive treatment that is used to ablate intracranial structures to treat mesial temporal lobe epilepsy (MTLE). Region of interest (ROI) segmentation before and after LITT would enable automated lesion quantification to objectively assess treatment efficacy. Deep learning techniques, such as convolutional neural networks (CNNs) are state-of-the-art solutions for ROI segmentation, but require large amounts of annotated data during the training. However, collecting large datasets from emerging treatments such as LITT is impractical. In this paper, we propose a progressive brain lesion synthesis framework (PAVAE) to expand both the quantity and diversity of the training dataset. Concretely, our framework consists of two sequential networks: a mask synthesis network and a mask-guided lesion synthesis network. To better employ extrinsic information to provide additional supervision during network training, we design a condition embedding block (CEB) and a mask embedding block (MEB) to encode inherent conditions of masks to the feature space. Finally, a segmentation network is trained using raw and synthetic lesion images to evaluate the effectiveness of the proposed framework. Experimental results show that our method can achieve realistic synthetic results and boost the performance of down-stream segmentation tasks above traditional data augmentation techniques.


page 7

page 9


Mask2Lesion: Mask-Constrained Adversarial Skin Lesion Image Synthesis

Skin lesion segmentation is a vital task in skin cancer diagnosis and fu...

CarveMix: A Simple Data Augmentation Method for Brain Lesion Segmentation

Brain lesion segmentation provides a valuable tool for clinical diagnosi...

Free-form Lesion Synthesis Using a Partial Convolution Generative Adversarial Network for Enhanced Deep Learning Liver Tumor Segmentation

Automatic deep learning segmentation models has been shown to improve bo...

Decoupling Shape and Density for Liver Lesion Synthesis Using Conditional Generative Adversarial Networks

Lesion synthesis received much attention with the rise of efficient gene...

Lesion Mask-based Simultaneous Synthesis of Anatomic and MolecularMR Images using a GAN

Data-driven automatic approaches have demonstrated their great potential...

Please sign up or login with your details

Forgot password? Click here to reset