Imbalance-Effective Active Learning in Nucleus, Lymphocyte and Plasma Cell Detection

Chao Ting Li, Hung Wen Tsai, Tseng Lung Yang, Jung Chi Lin, Nan Haw Chow, Yu Hen Hu, Kuo Sheng Cheng, Pau Choo Chung

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish
Title of host publicationInterpretable and Annotation-Efficient Learning for Medical Image Computing - 3rd International Workshop, iMIMIC 2020, 2nd International Workshop, MIL3iD 2020, and 5th International Workshop, LABELS 2020, Held in Conjunction with MICCAI 2020, Proceedings
EditorsJaime Cardoso, Wilson Silva, Ricardo Cruz, Hien Van Nguyen, Badri Roysam, Nicholas Heller, Pedro Henriques Abreu, Jose Pereira Amorim, Ivana Isgum, Vishal Patel, Kevin Zhou, Steve Jiang, Ngan Le, Khoa Luu, Raphael Sznitman, Veronika Cheplygina, Samaneh Abbasi, Diana Mateus, Emanuele Trucco
PublisherSpringer Science and Business Media Deutschland GmbH
Pages223-232
Number of pages10
ISBN (Print)9783030611651
DOIs
Publication statusPublished - 2020
Event3rd International Workshop on Interpretability of Machine Intelligence in Medical Image Computing, iMIMIC 2020, the 2nd International Workshop on Medical Image Learning with Less Labels and Imperfect Data, MIL3ID 2020, and the 5th International Workshop on Large-scale Annotation of Biomedical data and Expert Label Synthesis, LABELS 2020, held in conjunction with the 23rd International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2020 - Lima, Peru
Duration: 2020 Oct 42020 Oct 8

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12446 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference3rd International Workshop on Interpretability of Machine Intelligence in Medical Image Computing, iMIMIC 2020, the 2nd International Workshop on Medical Image Learning with Less Labels and Imperfect Data, MIL3ID 2020, and the 5th International Workshop on Large-scale Annotation of Biomedical data and Expert Label Synthesis, LABELS 2020, held in conjunction with the 23rd International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2020
Country/TerritoryPeru
CityLima
Period20-10-0420-10-08

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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