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

04/26/2019
by   Ludovic Venet, et al.
0

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.

READ FULL TEXT
research
07/07/2023

Matching in the Wild: Learning Anatomical Embeddings for Multi-Modality Images

Radiotherapists require accurate registration of MR/CT images to effecti...
research
12/27/2017

Geometry Processing of Conventionally Produced Mouse Brain Slice Images

Brain mapping research in most neuroanatomical laboratories relies on co...
research
07/29/2021

Automatic Multi-Stain Registration of Whole Slide Images in Histopathology

Joint analysis of multiple biomarker images and tissue morphology is imp...
research
10/05/2018

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...
research
04/08/2015

A Multicomponent Approach to Nonrigid Registration of Diffusion Tensor Images

We propose a nonrigid registration approach for diffusion tensor images ...
research
03/15/2022

A multi-organ point cloud registration algorithm for abdominal CT registration

Registering CT images of the chest is a crucial step for several tasks s...

Please sign up or login with your details

Forgot password? Click here to reset