# Predicting Post-Liposuction Body Shape Using RGB Image-to-Image Translation
## 3 Materials and Methods  
Figure 1 presents the proposed framework, which integrates data augmentation using CeGAN and image-to-image translation with Pix2 Pix to predict post-liposuction body shape from preoperative RGB images. Both real and augmented paired data are used to compensate for the limited sample size. Figure 1: Overall prediction framework. This figure illustrates the complete pipeline for predicting post-liposuction body shape using RGB images. The process begins with a paired dataset containing pre- and post-liposuction images and corresponding BMI values. To address the limited sample size, data augmentation is performed using a Continuous Conditional GAN (CcGAN), which generates synthetic images conditioned on continuous BMI values. A linear regression model estimates post-liposuction BMI from pre-liposuction BMI, enabling the generation of realistic pre- and postoperative image pairs for the same individual. The original and augmented datasets are then combined to train a Pix2 Pix-based image-to-image translation model, which predicts postoperative body shape from preoperative images. This framework enhances prediction accuracy and visual realism by integrating data augmentation and loss-function improvements. **(Data Collection)** Since post-liposuction appearance must be predicted using images captured before liposuction, data to be collected must satisfy several conditions: First, to clearly determine the change in body shape, the images must depict the subject with only underwear on. Second, image pairs depicting the same individual before and after liposuction are required. Accordingly, images of 230 patients who underwent liposuction were collected. This study's protocol was approved by the Institutional Review Board of Dongguk University (DUIRB-202202-14), and the relevant procedures complied with the principles of the Declaration of Helsinki. On the day of liposuction, the patient captured images of their upper and lower body in a fixed position from the front, left, right, and back; two months after liposuction, they captured the same images to record the postoperative changes. All images were captured with the camera 110 cm above the ground and 100 cm away from the heel. To ensure consistency in posture during image acquisition, all participants were instructed to stand with their arms naturally at their sides, feet shoulder-width apart, and eyes facing forward. However, due to the absence of explicit guidelines regarding arm angles or spacing between the arms and torso, individual variations in arm positioning occurred. This led to ambiguous boundaries between the abdomen and the arms in some cases. All images were captured in a closed studio environment without windows to eliminate the influence of natural light, using consistent lighting conditions and fixed camera settings. For participant safety and comfort, the entire process was supervised by medical professionals. A total of 920 images were collected, including front, back, left, and right views of the upper and lower body. Among these, 230 left-side upper body images were selected for model training and evaluation, as this viewpoint most clearly captured changes in the abdominal and flank areas and provided a distinct view of the target region for prediction. The images were taken under controlled conditions in a clinical environment using a DSLR camera (Canon EOS 800D (Canon Inc., Tokyo, Japan), equipped with a 24.2 MP APS-C sensor). All subjects were photographed against a matte white background, and the lighting setup followed a three-point lighting system (left and right-side lights and a front-facing soft light) to minimize skin reflections and shadow artifacts. Continuous lighting with a color temperature of 5500 K was used, and no flash was applied. Additionally, before each session, subjects were instructed to remain under the lighting for five seconds to allow their skin tone to adjust to the environment. Lighting intensity and camera exposure settings were kept consistent across all sessions.