Enhancing Surgical Visualization: Feasibility Study on GAN-Based Image Generation for Post Operative Cleft Palate Images

Daniel Atputharuban, Christoph Theopold, Aonghus Lawlor

2024

Abstract

Cleft Lip/Palate (CL/P) is a prevalent maxillofacial congenital anomaly arising from the failure of fusion in the frontonasal and maxillary processes. Currently, no internationally agreed gold standard procedures for cleft lip repair exists, and surgical approaches are frequently selected based on the surgeon’s past experiences and the specific characteristics of individual patient cases. The Asher-McDade score, a widely employed tool in assessing unilateral cleft lip surgeries, relies on criteria related to aesthetics and symmetry of maxillofacial region. However, no objective metric has been developed for assessing surgical success. This study aims to incorporate deep learning and Generative Adversarial Network (GAN) methods to construct an image generation framework to produce post-operative lip images that can serve as a standardized reference for assessing surgical success. We introduce an image similarity score based on the image embeddings which we use to validate the generated images. Our method paves the way to a set of techniques for the generation of synthetic faces which can guide surgeons in assessing the outcomes of CL/P surgery.

Paper Citation

in Harvard Style

Atputharuban D., Theopold C. and Lawlor A. (2024). Enhancing Surgical Visualization: Feasibility Study on GAN-Based Image Generation for Post Operative Cleft Palate Images. In Proceedings of the 13th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM; ISBN 978-989-758-684-2, SciTePress, pages 939-945. DOI: 10.5220/0012576900003654

in Bibtex Style

@conference{icpram24,
author={Daniel Atputharuban and Christoph Theopold and Aonghus Lawlor},
title={Enhancing Surgical Visualization: Feasibility Study on GAN-Based Image Generation for Post Operative Cleft Palate Images},
booktitle={Proceedings of the 13th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM},
year={2024},
pages={939-945},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012576900003654},
isbn={978-989-758-684-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 13th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM
TI - Enhancing Surgical Visualization: Feasibility Study on GAN-Based Image Generation for Post Operative Cleft Palate Images
SN - 978-989-758-684-2
AU - Atputharuban D.
AU - Theopold C.
AU - Lawlor A.
PY - 2024
SP - 939
EP - 945
DO - 10.5220/0012576900003654
PB - SciTePress