Medical image analysis and medical information retrieval, with and without deep learning
Brown Bag Lecture by Dr. Oge Marques | 10/9/2018 11:00AM – 12PM | 7th Floor Conference Room, Bldg 38A
The field of medical image analysis has experienced a significant shift towards deep learning approaches, particularly convolutional neural networks (CNNs), in recent years. Thanks to their ability to learn features, representations, and tasks directly from images – thereby eliminating the need for manual feature extraction and selection – deep learning solutions are becoming ever more prevalent.
For broader applications, such as Medical Case Retrieval (MCR), there are numerous technical challenges that must be addressed for which deep learning may not be the answer.
In this talk I will present a brief overview of my work in topics related to medical image analysis and medical information retrieval, with and without deep learning, with highlights from recent collaborative work in three distinct areas: (1) tuberculosis type classification; (2) skin lesion segmentation and classification; and (3) concept-based and multimodal methods for MCR.
Oge Marques, PhD is Professor of Computer Science and Engineering at the College of Engineering and Computer Science and, by courtesy, Professor of Information Technology and Operations Management at the College of Business, at Florida Atlantic University (FAU) (Boca Raton, Florida, USA). He is Tau Beta Pi Eminent Engineer, ACM Distinguished Speaker, and the author of more than 100 publications in the area of intelligent processing of visual information – which combines the fields of image processing, computer vision, image retrieval, machine learning, serious games, and human visual perception –, including the textbook “Practical Image and Video Processing Using MATLAB” (Wiley-IEEE Press). Professor Marques is Senior Member of both the IEEE (Institute of Electrical and Electronics Engineers) and the ACM (Association for Computing Machinery) and member of the honor societies of Sigma Xi, Phi Kappa Phi and Upsilon Pi Epsilon. He has more than 30 years of teaching and research experience in different countries (USA, Austria, Brazil, France, India, Spain, Serbia, and the Netherlands).
For additional information: http://ogemarques.com/