Abstract. An Imbalance-Effective Active Learning (IEAL) based deep neural network algorithm is proposed for the automatic detection of nucleus, lymphocyte and plasma cells in hepatitis diagnosis. The active sampling approach reduces the training sample annotation cost and mitigates extreme imbalances among the nucleus, lymphocytes and plasma samples. A Bayesian U-net model is developed by incorporating IEAL with basic U-Net. The testing results obtained using an in-house dataset consisting of 43 whole slide images (300 256*256 images) show that the proposed method achieves an equal or better performance compared than a basic U-net classifier using less than half the number of annotated samples.
Pau-Choo (Julia) Chung (S’89-M’91-SM’02-F’08) received the Ph.D. degree in electrical engineering from
Dr. Chung’s research interests include computational intelligence, medical image analysis, video analysis, and pattern recognition. Dr. Chung participated in many international conferences and society activities. She served as the program committee member in many international conferences. She served as the Publicity Co-Chair of WCCI 2014, SSCI 2013, SSCI 2011, and WCCI 2010. She served as an Associate Editor of IEEE Transactions on Neural Network and Learning Systems(2013-2015) and the Associate Editor of IEEE Transactions on Biomedical Circuits and Systems.
Dr. Chung was the Chair of IEEE Computational Intelligence Society (CIS) (2004-2005) in Tainan Chapter, the Chair of the IEEE Life Science Systems and Applications Technical Committee (2008-2009). She was a member in BoG of CAS Society (2007-2009, 2010-2012). She served as an IEEE CAS Society Distinguished Lecturer (2005-2007) and the Chair of CIS Distinguished Lecturer Program (2012-2013). She served on two terms of ADCOM member of IEEE CIS (2009-2011, 2012-2014), the Chair of IEEE CIS Women in CI (2014). She is a Member of Phi Tau Phi honor society and is an IEEE Fellow since 2008.