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Big data based spine disease progression prediction

Department of Orthopaedics & Traumatology

Applications accepted all year round Funded PhD Project (Students Worldwide)

About the Project

Our team has established a big dataset with spine MRIs and clinical labels, as well as developed automated novel pipelines for feature detection and segmentation. Our methods include conventional machine learning and deep learning, image processing, etc. These novel approaches can significantly reduce the manual workload of clinical practice as well as provide consistent results. We are looking for a suitable candidate to expand the dataset and established a systematic registry that contains comprehensive medical data, including image (MRI, CT, Xray), clinical information, and follow-up, for multi-domain big data analysis tasks in spine clinic. Technically, a data structure for the organization, storage, and translation of the dataset needs to be designed. Research involves in human machines interactions resulting in a clinical friendly UI interface module of the dataset to the upload and download the data flexibly for different tasks, with encryption, such as image enhancement, auto-diagnosis, image segmentation, pathology predication. Our center is the one of the largest spine centers in Hong Kong and routinely screen over 200 patients with spine disorders per week. This presents a guaranteed opportunity for satisfied patient sample size for this project.

Graduated from the University of Hong Kong with a Bachelor of medicine and bachelor of surgery (MBBS), Dr. Jason Cheung trained as an Orthopaedic Surgeon at the Queen Mary Hospital. He is a Clinical Associate Professor with the Department of Orthopaedics and Traumatology at the University of Hong Kong. His main research interests are paediatric growth and spinal deformity, developmental lumbar spinal stenosis, management of cervical myelopathy and orthopaedic infections.

Supervisor’s information webpage link:;jsessionid=BCE9E95E487FB848A511C6E1C8B85C1A

Faculty information, funding opportunities and application deadlines:

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