Collaborative Adversarial Networks for Joint Synthesis and Segmentation of X-ray Breast Mass Images | |
Shen, Tianyu1,2; Gou, Chao4; Wang, Jiangong1,2; Wang, Fei-Yue1,3 | |
2021-01-29 | |
会议日期 | 2020-11-06 |
会议地点 | Shanghai, China |
关键词 | generative adversarial network medical image synthesis mass segmentation X-ray breast mass |
英文摘要 | In this paper, we propose Collaborative Adversarial Networks (CAN) to enable simultaneous forward synthesis and backward segmentation of X-ray breast mass image. The proposed CAN consists of a generator (G), an inverter (I) and a discriminator (D). G aims to reconstruct mass images from corresponding annotated masks, while I is trained for mapping images back to accurate segmentation masks. All the obtained mask-image pairs are fed to D trained in an adversarial learning scheme. Through the collaborative adversarial training using a joint loss function, G synthesizes realistic mass images consistent with provided masks and I effectively segments the tumor regions from the images. Qualitative and quantitative evaluations on publicly available INbreast database demonstrate the effectiveness of our model. Furthermore, different from conventional GANs-based methods that can only perform either image synthesis or segmentation, the proposed model can be generalized to other bidirectional image-to-image translation of multimodal medical data. |
内容类型 | 会议论文 |
源URL | [http://ir.ia.ac.cn/handle/173211/44769] |
专题 | 自动化研究所_复杂系统管理与控制国家重点实验室_先进控制与自动化团队 |
通讯作者 | Gou, Chao |
作者单位 | 1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 3.Qingdao Acad Intelligent Ind, Zhilidao Rd 1, Qingdao 266000, Shandong, Peoples R China 4.Sun Yat Sen Univ, Sch Intelligent Syst Engn, Guangzhou, Peoples R China |
推荐引用方式 GB/T 7714 | Shen, Tianyu,Gou, Chao,Wang, Jiangong,et al. Collaborative Adversarial Networks for Joint Synthesis and Segmentation of X-ray Breast Mass Images[C]. 见:. Shanghai, China. 2020-11-06. |
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