June 2020

Early Diagnosis of Scoliosis in Children from RGB-D Images Using Deep Learning

Scoliosis is typically diagnosed from X-ray images, but diagnostic X-rays increase the risk of developmental problems and cancer in those exposed. This project aims to eliminate children’s X-ray exposure in the early diagnosis of scoliosis by generating X-ray images of children’s backs from the corresponding harmless RGB-D images. In this project, a deep learning model based on HRNet was built and trained to detect landmark locations of the backs on the RGB-D images first. With the detected landmarks, the X-ray images of the children’s backs were eventually synthesized from the corresponding RGB-D images by another deep learning model that was built and trained based on the pix2pix model.

Automatic Chair Stacking System

Automation is the technology about combination of hardware and software to complete designated tasks with minimal manual intervention. Automation was first applied to automobile industry in the 1970s and started to extend its use in daily life since then. Automatic system has its advantages over traditional manpower in doing repetitive tasks, e.g., it maintains a high-quality standard and safety standard.

This project, the Automatic Chair Stacking System, will be cooperating with the Automatic Chair Parking System to showcase the idea of automatic conference room, i.e., to automatically set up chairs in the area.