We present a software that predicts non-cleft facial images for patients with
cleft lip, thereby facilitating the understanding, awareness and discussion of
cleft lip surgeries. To protect patients privacy, we design a software
framework using image inpainting, which does not require cleft lip images for
training, thereby mitigating the risk of model leakage. We implement a novel
multi-task architecture that predicts both the non-cleft facial image and
facial landmarks, resulting in better performance as evaluated by surgeons. The
software is implemented with PyTorch and is usable with consumer-level color
images with a fast prediction speed, enabling effective deployment.

我们提出了一种软件，可预测无腭裂唇病患的非腭裂面部图像，从而促进对腭裂唇手术的理解、意识和讨论。我们采用图像修补设计了一个软件框架，不需要腭裂唇图像进行训练，从而减轻了模型泄漏的风险。我们实现了一种新颖的多任务架构，预测非腭裂面部图像和面部关键点，表现更好，由外科医生评估。该软件采用 PyTorch 实现，在消费级彩色图像上可使用，预测速度快，实现了有效的部署。