Volume 11 Issue 5
Open-source software for 3D morphing in facial plastic surgery and research on facial landmark detection, along with an open-access dataset derived from synthetic 3D models generated through deep learning (AI)
1Madiha Ahsan, 2Dr. Muhammad Hamza Hashmi, 3Kashif Lodhi, 4Khurram Shahzad
1Resident Plastic Surgeon (final year), Burns and Plastic surgery Centre, Peshawar
2Avicenna Dental College Lahore
3Department of Agricultural, Food and Environmental Sciences. Università Politécnica delle Marche Via Brecce Bianche 10, 60131 Ancona (AN) Italy
4HIESS, Hamdard University, Karachi, Pakistan
ABSTRACT
Background: Facial plastic surgery and facial landmark detection are critical components of medical and computer vision research. This study introduces “FacialMorphAI,” an innovative open-source 3D morphing software designed to revolutionize facial plastic surgery simulations and facial landmark detection methodologies. The motivation stems from the need for accessible tools in the medical and research communities that enhance facial analysis and surgical planning.
Aim: The primary aim of this research is to develop an advanced open-source 3D morphing software catering to the specific needs of facial plastic surgery and facial landmark detection. Additionally, the study seeks to create an open-access face dataset utilizing deep learning-generated synthetic 3D models, contributing valuable resources for training and testing facial recognition algorithms.
Methods: FacialMorphAI is implemented using state-of-the-art deep learning techniques to enable accurate 3D morphing simulations. The software leverages artificial intelligence to generate realistic facial expressions, facilitating precise facial plastic surgery predictions. The methodology also involves the creation of a diverse open-access face dataset, generated through deep learning techniques, ensuring the inclusion of various facial features and expressions.
Results: The implementation of FacialMorphAI demonstrates its efficacy in providing realistic 3D morphing for facial plastic surgery applications and accurate facial landmark detection. The open-access face dataset serves as a valuable resource for researchers and practitioners, fostering advancements in facial recognition technologies. Results showcase the potential impact of synthetic 3D models in training robust and versatile facial analysis algorithms.
Conclusion: This research contributes an open-source 3D morphing tool, FacialMorphAI, addressing the specific needs of facial plastic surgery and facial landmark detection research. The accompanying open-access face dataset enhances the availability of diverse facial data for the development and evaluation of deep learning models. The combined efforts aim to propel advancements in medical imaging, facial analysis, and artificial intelligence applications related to facial features.
Keywords: Open-Source Software, 3D Morphing, Facial Plastic Surgery, Facial Landmark Detection, Deep Learning, Artificial Intelligence, Synthetic 3D Models, Face Dataset, Medical Imaging, Facial Analysis.