2023/05/17 by Shuang Chen, Chen, Shuang, Amir Atapour–Abarghouei +5
Biochemistry, Genetics and Molecular Biology · Medicine · #Cervical Cancer and HPV Research #Cleft Lip and Palate Research #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Facial Rejuvenation and Surgery Techniques
paper · pdf · doi:10.48550/arxiv.2305.10589
openalex publication_date 2023/05/17 · openalex created_date 2023/05/21 · openalex updated_date 2026/07/28
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.