2019
DOI: 10.1101/849570
|View full text |Cite
Preprint
|
Sign up to set email alerts
|

Tensor Image Registration Library: Automated Non-Linear Registration of Sparsely Sampled Histological Specimens to Post-Mortem MRI of the Whole Human Brain

Abstract: Highlights 29 30• TIRL: new framework for prototyping bespoke image registration pipelines 31• Pipeline for automated registration of small-slide histology to whole-brain MRI 32• Slice-to-volume registration accounting for through-plane deformations 33• No need for serial histological sampling 34 35Abstract 36 37 There is a need to understand the histopathological basis of MRI signal characteristics in 38 complex biological matter. Microstructural imaging holds promise for sensitive and specific 39 indicator… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

0
39
0

Year Published

2020
2020
2023
2023

Publication Types

Select...
5
3

Relationship

5
3

Authors

Journals

citations
Cited by 13 publications
(39 citation statements)
references
References 62 publications
(61 reference statements)
0
39
0
Order By: Relevance
“…Comparisons between ALS and control brains over the corpus callosum (c) reveal changes in fractional anisotropy (FA, normalised to Par/Temp/Occ lobe), with biggest changes associated with motor regions (Hofer & Frahm, 2006) ( * = p < 0.05; * * = p < 0.05 following multiple comparison correction). Accurate MRI-histology coregistrations facilitates cross-modality comparisons, and (d) displays an example MRI-histology coregistration over the visual cortex of a single ALS brain achieved using the Tensor Image Registration Library (TIRL) (Huszar et al, 2019 (Jucker & Walker, 2013).…”
Section: Digital Brain Zoomentioning
confidence: 99%
See 1 more Smart Citation
“…Comparisons between ALS and control brains over the corpus callosum (c) reveal changes in fractional anisotropy (FA, normalised to Par/Temp/Occ lobe), with biggest changes associated with motor regions (Hofer & Frahm, 2006) ( * = p < 0.05; * * = p < 0.05 following multiple comparison correction). Accurate MRI-histology coregistrations facilitates cross-modality comparisons, and (d) displays an example MRI-histology coregistration over the visual cortex of a single ALS brain achieved using the Tensor Image Registration Library (TIRL) (Huszar et al, 2019 (Jucker & Walker, 2013).…”
Section: Digital Brain Zoomentioning
confidence: 99%
“…MRI and microscopy) datasets on the Digital Brain Bank website is achieved with Tview. An example Tview implementation is available at open.win.ox.ac.uk/DigitalBrainBank/#/tileviewer, where cross-modality coregistrations were performed using the Tensor Image Registration Library (TIRL) (Huszar et al, 2019) and FNIRT (Andersson, Jenkinson, Smith, & others, 2007;Jenkinson, Beckmann, Behrens, Woolrich, & Smith, 2012), both available as part of FSL. Code for Tview is available at https://git.fmrib.ox.ac.uk/thanayik/slideviewer.…”
Section: Tviewmentioning
confidence: 99%
“…Second, registration between histology slides and MRI data was not performed, requiring us to correlate at the level of region-of-interest rather than pixel-wise. A pipeline that enables automated registration of histology slides to 3D MRI images using dissection photos as an intermediary is currently under development ( Huszar et al., 2019 ). This registration pipeline aims to enable pixel-wise comparisons between MRI and histology acquired within the same sample.…”
Section: Discussionmentioning
confidence: 99%
“…Second, registration between histology slides and MRI data was not performed, requiring us to correlate at the level of region-of-interest rather than pixel-wise. A pipeline that enables automated registration of histology slides to 3D MRI images using dissection photos as an intermediary is currently under development [56].…”
Section: Discussionmentioning
confidence: 99%