Automatic Multi-Stain Registration of Whole Slide Images in Histopathology

by   Abubakr Shafique, et al.

Joint analysis of multiple biomarker images and tissue morphology is important for disease diagnosis, treatment planning and drug development. It requires cross-staining comparison among Whole Slide Images (WSIs) of immuno-histochemical and hematoxylin and eosin (H E) microscopic slides. However, automatic, and fast cross-staining alignment of enormous gigapixel WSIs at single-cell precision is challenging. In addition to morphological deformations introduced during slide preparation, there are large variations in cell appearance and tissue morphology across different staining. In this paper, we propose a two-step automatic feature-based cross-staining WSI alignment to assist localization of even tiny metastatic foci in the assessment of lymph node. Image pairs were aligned allowing for translation, rotation, and scaling. The registration was performed automatically by first detecting landmarks in both images, using the scale-invariant image transform (SIFT), followed by the fast sample consensus (FSC) protocol for finding point correspondences and finally aligned the images. The Registration results were evaluated using both visual and quantitative criteria using the Jaccard index. The average Jaccard similarity index of the results produced by the proposed system is 0.942 when compared with the manual registration.



There are no comments yet.


page 2

page 3

page 4


Regional Registration of Whole Slide Image Stacks Containing Highly Deformed Artefacts

Motivation: High resolution 2D whole slide imaging provides rich informa...

Performance of Image Registration Tools on High-Resolution 3D Brain Images

Recent progress in tissue clearing has allowed for the imaging of entire...

Map3D: Registration Based Multi-Object Tracking on 3D Serial Whole Slide Images

There has been a long pursuit for precise and reproducible glomerular qu...

Accurate and Robust Alignment of Variable-stained Histologic Images Using a General-purpose Greedy Diffeomorphic Registration Tool

Variously stained histology slices are routinely used by pathologists to...

Morphological Change Forecasting for Prostate Glands using Feature-based Registration and Kernel Density Extrapolation

Organ morphology is a key indicator for prostate disease diagnosis and p...

Generative Modeling with Conditional Autoencoders: Building an Integrated Cell

We present a conditional generative model to learn variation in cell and...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.