The Big Data Analytics Center (BIDAC)

Real-time adaptive brachytherapy treatment planning system based on multi-modality image guidance for cervical cancer

PI – Nazar Zaki, College of Information Technology, UAE University, Al Ain, UAE

Co-PI - Wenjian Qin, The Shenzhen Institutes of Advanced Technology (SIAT), Chinese Academy of Science (CAS)

Duration 2 Years

Cervical cancer is the second leading cause of death among women in developing countries. Nearly 70% of cervical cancer deaths occur in east, central, and South Asia. The deaths of the disease among UAE women doubled in the last 6 years. In 2018, over 7,600 women in the Mena region had tragically died from cervical cancer according to the latest data from the International Agency for Research on Cancer (IARC), published in the Global Cancer Observatory. Through advanced Artificial Intelligence techniques, this project will use prior information (such as diagnostic nuclear magnetic resonance/CT images) for automatic and accurate segmentation and multi-modal image registration to improve the MR-based cervical cancer diagnosis. Intelligent multi-modal image guidance in distance therapy is expected to help to generate the best individualized conformal radiotherapy plan and reduce the radiotherapy-related toxicity of intraluminal organs. This proposed project has important significance to the UAE and the Chinese community. The visibility, high-quality publications, and collaborations between the UAEU and the Chinese Academy of Science (CAS) will put the UAE at the forefront of Cancer Research. The project will generate results, which UAE will leverage in future projects with a vision to make significant contributions to healthcare.

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