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| Home > Publications database > Rigid and non-rigid registration of polarized light imaging data for 3D reconstruction of the temporal lobe of the human brain at micrometer resolution > print |
| Home > Publications database > Rigid and non-rigid registration of polarized light imaging data for 3D reconstruction of the temporal lobe of the human brain at micrometer resolution > print |
| 001 | 851327 | ||
| 005 | 20210129234843.0 | ||
| 024 | 7 | _ | |a 10.1016/j.neuroimage.2018.06.084 |2 doi |
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| 100 | 1 | _ | |a Ali, Sharib |0 P:(DE-HGF)0 |b 0 |e Corresponding author |
| 245 | _ | _ | |a Rigid and non-rigid registration of polarized light imaging data for 3D reconstruction of the temporal lobe of the human brain at micrometer resolution |
| 260 | _ | _ | |a Orlando, Fla. |c 2018 |b Academic Press |
| 336 | 7 | _ | |a article |2 DRIVER |
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| 520 | _ | _ | |a To understand the spatial organization as well as long- and short-range connections of the human brain at microscopic resolution, 3D reconstruction of histological sections is important. We approach this challenge by reconstructing series of unstained histological sections of multi-scale (1:3 μm and 64 μm) and multi-modal 3D polarized light imaging (3D-PLI) data. Since spatial coherence is lost during the sectioning procedure, image registration is the major step in 3D reconstruction. We propose a non-rigid registration method which comprises of a novel multi-modal similarity metric and an improved regularization scheme to cope with deformations inevitably introduced during the sectioning procedure, as well as a rigid registration approach using a robust similarity metric for improved initial alignment. We also introduce a multi-scale feature-based localization and registration approach for mapping of 1:3 μm sections to 64 μm sections and a scale-adaptive method that can handle challenging sections with large semi-global deformations due to tissue splits. We have applied our registration method to 126 consecutive sections of the temporal lobe of the human brain with 64 μm and 1:3 μm resolution. Each step of the registration method was quantitatively evaluated using 10 different sections and manually determined ground truth, and a quantitative comparison with previous methods was performed. Visual assessment of the reconstructed volumes and comparison with reference volumes confirmed the high quality of the registration result. |
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| 536 | _ | _ | |a 3D Reconstruction of Nerve Fibers in the Human, the Monkey and the Rodent Brain (jinm11_20171101) |0 G:(DE-Juel1)jinm11_20171101 |c jinm11_20171101 |f 3D Reconstruction of Nerve Fibers in the Human, the Monkey and the Rodent Brain |x 3 |
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| 700 | 1 | _ | |a Rohr, Karl |0 P:(DE-HGF)0 |b 5 |e Last author |
| 773 | _ | _ | |a 10.1016/j.neuroimage.2018.06.084 |0 PERI:(DE-600)1471418-8 |p 235-251 |t NeuroImage |v 181 |y 2018 |x 1053-8119 |
| 856 | 4 | _ | |u https://juser.fz-juelich.de/record/851327/files/1-s2.0-S1053811918305913-main.pdf |y Restricted |
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| 856 | 4 | _ | |u https://juser.fz-juelich.de/record/851327/files/YNIMG_15090_ALIetal-1.pdf |y Published on 2018-11-01. Available in OpenAccess from 2019-11-01. |
| 856 | 4 | _ | |u https://juser.fz-juelich.de/record/851327/files/YNIMG_15090_ALIetal-1.pdf?subformat=pdfa |x pdfa |y Published on 2018-11-01. Available in OpenAccess from 2019-11-01. |
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