Yu-Hua Fang PhD

Yu-Hua Fang PhD

Open Datasets of Medical Imaging: Impact on Neurodegenerative Diseases and Cancer Research
Associate Professor
Department of Radiology, University of Alabama at Birmingham
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Abstract 

Data sharing on the public domain for imaging datasets and studies has deeply and critically impacted on medical imaging research. As large imaging datasets are typically difficult to obtain, open datasets allow researchers to develop and evaluate novel imaging processing methods, especially over machine learning or deep learning models. In this talk, we will examine a few examples of public imaging datasets and websites, examine how they influenced research and clinical applications, and discuss about their limitations. We will also probe future possibilties of further expanding the data sharing in imaging communities and how to maximize its benefits for developing new diagnostic tools or therapies. Applications will be reviewed for cancer and neurology research. With this talk, we wish to recognize the importance of data sharing in imaging research and encourage more investigators and institutions to consider sharing their data to promote more advanced research in precise medicine. 

 

Biography 

Research of Dr. Yu-Hua Fang focuses on biomedical image processing, analysis and quantification for precision medicine. He has been leading his research group to develop image processing algorithms and advanced image-derived features, either hand-crafted or through deep learning, for image classification and patient outcome prediction in making personalized and precise medical decisions. He has utilized various advanced image processing techniques, including deep learning cross-modality registration, automated image segmentation, kinetic modeling analysis, texture analysis and convolutional neural networks to study challenging problems in clinical diagnosis and treatment planning over cancer, neural and cardiovascular diseases. His group has also been actively providing open-source software to the imaging community for research purposes on image processing and analysis.