Literature DB >> 21715143

Real-time deformable registration of multi-modal whole slides for digital pathology.

Dan Mueller1, Dirk Vossen, Bas Hulsken.   

Abstract

Digital pathology provides new ways to visualize tissue slides and enables new workflows for analyzing these slides. Analogous to radiology, adjacent tissue sections prepared with different stains or biomarkers (e.g. H&E, IHC, special stains, or ISH; chromogenic or fluorescent) may be seen as different modalities, each representing different structural and/or functional information. Today, the anatomic pathologist views multiple glass slides using an optical microscope and then combines the information in their head to reach a (diagnostic) opinion. Moreover, due to the nature of the slide preparation and digitization process, the tissue and its features do not have the exact same morphology, appearance, or spatial alignment, making it difficult to find the same region on adjacent slides. To address such concerns, this paper presents a method for the spatial alignment of multi-modal whole slide digital microscopy images. To remain practical, the described method employs a two-step registration strategy designed to reduce computation time: the first step computes a B-spline deformable transform on low-resolution images prior to visualization, the second step applies the precomputed transformation only to the high-resolution region currently being viewed. The proposed method is demonstrated using a number of cases comprising H&E and IHC stained slides. These results indicate the feasibility of deformable registration for spatial alignment of multi-modal whole slide digital microscopy images within practical time constraints.
Copyright © 2011 Elsevier Ltd. All rights reserved.

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Year:  2011        PMID: 21715143     DOI: 10.1016/j.compmedimag.2011.06.006

Source DB:  PubMed          Journal:  Comput Med Imaging Graph        ISSN: 0895-6111            Impact factor:   4.790


  6 in total

1.  Registration of whole immunohistochemical slide images: an efficient way to characterize biomarker colocalization.

Authors:  Xavier Moles Lopez; Paul Barbot; Yves-Rémi Van Eycke; Laurine Verset; Anne-Laure Trépant; Lionel Larbanoix; Isabelle Salmon; Christine Decaestecker
Journal:  J Am Med Inform Assoc       Date:  2014-08-14       Impact factor: 4.497

2.  Fast cross-staining alignment of gigapixel whole slide images with application to prostate cancer and breast cancer analysis.

Authors:  Ching-Wei Wang; Yu-Ching Lee; Muhammad-Adil Khalil; Kuan-Yu Lin; Cheng-Ping Yu; Huang-Chun Lien
Journal:  Sci Rep       Date:  2022-07-08       Impact factor: 4.996

3.  Hyper-Stain Inspector: A Framework for Robust Registration and Localised Co-Expression Analysis of Multiple Whole-Slide Images of Serial Histology Sections.

Authors:  Nicholas Trahearn; David Epstein; Ian Cree; David Snead; Nasir Rajpoot
Journal:  Sci Rep       Date:  2017-07-17       Impact factor: 4.379

4.  High-throughput adaptive sampling for whole-slide histopathology image analysis (HASHI) via convolutional neural networks: Application to invasive breast cancer detection.

Authors:  Angel Cruz-Roa; Hannah Gilmore; Ajay Basavanhally; Michael Feldman; Shridar Ganesan; Natalie Shih; John Tomaszewski; Anant Madabhushi; Fabio González
Journal:  PLoS One       Date:  2018-05-24       Impact factor: 3.240

5.  3D reconstruction of multiple stained histology images.

Authors:  Yi Song; Darren Treanor; Andrew J Bulpitt; Derek R Magee
Journal:  J Pathol Inform       Date:  2013-03-30

6.  A quantitative approach to evaluate image quality of whole slide imaging scanners.

Authors:  Prarthana Shrestha; R Kneepkens; J Vrijnsen; D Vossen; E Abels; B Hulsken
Journal:  J Pathol Inform       Date:  2016-12-30
  6 in total

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