A Bilinear Interpolation Based Approach for Optimizing Hematoxylin and Eosin Stained Microscopical Images

被引:0
|
作者
Kuru, Kaya
Girgin, Sertan
机构
来源
关键词
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Hematoxylin & Eosin (H&E) is a widely used staining technique in medical pathology for distinguishing nuclei and cytoplasm in tissues by dying them in different colors; this helps to ease the diagnosis process. However, usually the microscopic digital images obtained using this technique suffer from uneven lighting, i.e. poor Koehler illumination. The existing ad-hoc methods for correcting this problem generally work in RGB color model, and may result in both an unwanted color shift and loosing essential details in terms of the diagnosis. The aim of this study is to present an alternative method that remedies these deficiencies. We first identify the characteristics of uneven lighting in pathological images produced by using the H&E technique, and then show how the quality of these images can be improved by applying an interpolation based approach in the Lab color model without losing any important detail. The effectiveness of the proposed method is demonstrated on sample microscopic images.
引用
收藏
页码:168 / 178
页数:11
相关论文
共 50 条
  • [1] Color Normalization Approach to Adjust Nuclei Segmentation in Images of Hematoxylin and Eosin Stained Tissue
    Piorkowski, Adam
    Gertych, Arkadiusz
    INFORMATION TECHNOLOGY IN BIOMEDICINE (ITIB 2018), 2019, 762 : 393 - 406
  • [2] Novel Color Normalization Method for Hematoxylin & Eosin Stained Histopahology Images
    Roy, Santanu
    Lal, Shyam
    Kini, Jyoti R.
    IEEE ACCESS, 2019, 7 : 28982 - 28998
  • [3] Automated epidermis segmentation in histopathological images of human skin stained with hematoxylin and eosin
    Kleczek, Pawel
    Dyduch, Grzegorz
    Jaworek-Korjakowska, Joanna
    Tadeusiewicz, Ryszard
    MEDICAL IMAGING 2017: DIGITAL PATHOLOGY, 2017, 10140
  • [4] Enhanced Visualization of Hematoxylin and Eosin Stained Pathological Characteristics by Phasor Approach
    Luo, Teng
    Lu, Yuan
    Liu, Shaoxiong
    Lin, Danying
    Qu, Junle
    ANALYTICAL CHEMISTRY, 2017, 89 (17) : 9224 - 9231
  • [5] The utility of color normalization for AI-based diagnosis of hematoxylin and eosin-stained pathology images
    Boschman, Jeffrey
    Farahani, Hossein
    Darbandsari, Amirali
    Ahmadvand, Pouya
    Van Spankeren, Ashley
    Farnell, David
    Levine, Adrian B.
    Naso, Julia R.
    Churg, Andrew
    Jones, Steven J. M.
    Yip, Stephen
    Kobel, Martin
    Huntsman, David G.
    Gilks, C. Blake
    Bashashati, Ali
    JOURNAL OF PATHOLOGY, 2022, 256 (01): : 15 - 24
  • [6] Dataset of segmented nuclei in hematoxylin and eosin stained histopathology images of ten cancer types
    Le Hou
    Rajarsi Gupta
    John S. Van Arnam
    Yuwei Zhang
    Kaustubh Sivalenka
    Dimitris Samaras
    Tahsin M. Kurc
    Joel H. Saltz
    Scientific Data, 7
  • [7] Dataset of segmented nuclei in hematoxylin and eosin stained histopathology images of ten cancer types
    Hou, Le
    Gupta, Rajarsi
    Van Arnam, John S.
    Zhang, Yuwei
    Sivalenka, Kaustubh
    Samaras, Dimitris
    Kurc, Tahsin M.
    Saltz, Joel H.
    SCIENTIFIC DATA, 2020, 7 (01)
  • [8] Comprehensive Experiments on Breast Cancer Hematoxylin and Eosin-stained Images Using UNet
    Jackson, Emily
    Le, Faye
    Lisbon, Je'Dae I.
    Coleman, Max
    Burman, Jordyn
    Wonderley, Astrid
    Eshaghian, Sepehr
    Lee, Sanghoon
    PROCEEDINGS OF THE 2024 ACM SOUTHEAST CONFERENCE, ACMSE 2024, 2024, : 121 - 128
  • [9] Quantification of Decellularization in Hematoxylin and Eosin Stained Images of Decellularized Aorta Using Machine Learning
    Nakamura, Naoko
    Yasuda, Eri
    Akiyama, Shota
    Hashimoto, Yoshihide
    Kishida, Akio
    Kimura, Tsuyoshi
    ADVANCED BIOMEDICAL ENGINEERING, 2024, 13 : 26 - 34
  • [10] Optimization and enhancement of H&E stained microscopical images by applying bilinear interpolation method on lab color mode
    Kuru, Kaya
    THEORETICAL BIOLOGY AND MEDICAL MODELLING, 2014, 11