A Multi-View Dynamic Fusion Framework: How to Improve the Multimodal Brain Tumor Segmentation from Multi-Views?

no code implementations • 21 Dec 2020 • Yi Ding, Wei Zheng, Guozheng Wu, Ji Geng, Mingsheng Cao, Zhiguang Qin

Moreover, the multi-view fusion loss, which consists of the segmentation loss, the transition loss and the decision loss, is proposed to facilitate the training process of multi-view learning networks so as to keep the consistency of appearance and space, not only in the process of fusing segmentation results, but also in the process of training the learning network.

Brain Tumor Segmentation MULTI-VIEW LEARNING +2

DeepKeyGen: A Deep Learning-based Stream Cipher Generator for Medical Image Encryption and Decryption

no code implementations • 21 Dec 2020 • Yi Ding, Fuyuan Tan, Zhen Qin, Mingsheng Cao, Kim-Kwang Raymond Choo, Zhiguang Qin

In this paper, a novel deep learning-based key generation network (DeepKeyGen) is proposed as a stream cipher generator to generate the private key, which can then be used for encrypting and decrypting of medical images.

Generative Adversarial Network

DeepEDN: A Deep Learning-based Image Encryption and Decryption Network for Internet of Medical Things

no code implementations • 12 Apr 2020 • Yi Ding, Guozheng Wu, Dajiang Chen, Ning Zhang, Linpeng Gong, Mingsheng Cao, Zhiguang Qin

Specifically, in DeepEDN, the Cycle-Generative Adversarial Network (Cycle-GAN) is employed as the main learning network to transfer the medical image from its original domain into the target domain.

Generative Adversarial Network