Accurate and Robust Alignment of Differently Stained Histologic Images Based on Greedy Diffeomorphic Registration.
Appl Sci (Basel)
; 11(4)2021 Feb.
Article
em En
| MEDLINE
| ID: mdl-34290888
ABSTRACT
Histopathologic assessment routinely provides rich microscopic information about tissue structure and disease process. However, the sections used are very thin, and essentially capture only 2D representations of a certain tissue sample. Accurate and robust alignment of sequentially cut 2D slices should contribute to more comprehensive assessment accounting for surrounding 3D information. Towards this end, we here propose a two-step diffeomorphic registration approach that aligns differently stained histology slides to each other, starting with an initial affine step followed by estimating a deformation field. It was quantitatively evaluated on ample (n = 481) and diverse data from the automatic non-rigid histological image registration challenge, where it was awarded the second rank. The obtained results demonstrate the ability of the proposed approach to robustly (average robustness = 0.9898) and accurately (average relative target registration error = 0.2%) align differently stained histology slices of various anatomical sites while maintaining reasonable computational efficiency (<1 min per registration). The method was developed by adapting a general-purpose registration algorithm designed for 3D radiographic scans and achieved consistently accurate results for aligning high-resolution 2D histologic images. Accurate alignment of histologic images can contribute to a better understanding of the spatial arrangement and growth patterns of cells, vessels, matrix, nerves, and immune cell interactions.
Texto completo:
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Base de dados:
MEDLINE
Idioma:
En
Revista:
Appl Sci (Basel)
Ano de publicação:
2021
Tipo de documento:
Article
País de afiliação:
Estados Unidos