Log In Sign Up

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

by   Ludovic Venet, et al.

Variously stained histology slices are routinely used by pathologists to assess extracted tissue samples from various anatomical sites and determine the presence or extent of a disease. Evaluation of sequential slides is expected to enable a better understanding of the spatial arrangement and growth patterns of cells and vessels. In this paper we present a practical two-step approach based on diffeomorphic registration to align digitized sequential histopathology stained slides to each other, starting with an initial affine step followed by the estimation of a detailed deformation field.


Robust, fast and accurate: a 3-step method for automatic histological image registration

We present a 3-step registration pipeline for differently stained histol...

Geometry Processing of Conventionally Produced Mouse Brain Slice Images

Brain mapping research in most neuroanatomical laboratories relies on co...

Automatic Multi-Stain Registration of Whole Slide Images in Histopathology

Joint analysis of multiple biomarker images and tissue morphology is imp...

AIRNet: Self-Supervised Affine Registration for 3D Medical Images using Neural Networks

In this work, we propose a self-supervised learning method for affine im...

Regional Registration of Whole Slide Image Stacks Containing Highly Deformed Artefacts

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

A Multicomponent Approach to Nonrigid Registration of Diffusion Tensor Images

We propose a nonrigid registration approach for diffusion tensor images ...