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Three-dimensional visualization of the functional fascicular groups of a long-segment peripheral nerve.

Abstract：

:The three-dimensional (3D) visualization of the functional bundles in the peripheral nerve provides direct and detailed intraneural spatial information. It is useful for selecting suitable surgical methods to repair nerve defects and in optimizing the construction of tissue-engineered nerve grafts. However, there remain major technical hurdles in obtaining, registering and interpreting 2D images, as well as in establishing 3D models. Moreover, the 3D models are plagued by poor accuracy and lack of detail and cannot completely reflect the stereoscopic microstructure inside the nerve. To explore and help resolve these key technical problems of 3D reconstruction, in the present study, we designed a novel method based on re-imaging techniques and computer image layer processing technology. A 20-cm ulnar nerve segment from the upper arm of a fresh adult cadaver was used for acetylcholinesterase (AChE) staining. Then, 2D panoramic images were obtained before and after AChE staining under the stereomicroscope. Using layer processing techniques in Photoshop, a space transformation method was used to fulfill automatic registration. The contours were outlined, and the 3D rendering of functional fascicular groups in the long-segment ulnar nerve was performed with Amira 4.1 software. The re-imaging technique based on layer processing in Photoshop produced an image that was detailed and accurate. The merging of images was accurate, and the whole procedure was simple and fast. The least square support vector machine was accurate, with an error rate of only 8.25%. The 3D reconstruction directly revealed changes in the fusion of different nerve functional fascicular groups. IN CONCLUSION:The technique is fast with satisfactory visual reconstruction.

journal_name

Neural Regen Res

journal_title

Neural regeneration research

authors

Qi J,Wang WY,Zhong YC,Zhou JM,Luo P,Tang P,He CF,Zhu S,Liu XL,Zhang Y

doi

10.4103/1673-5374.235307

subject

Has Abstract

pub_date

2018-08-01 00:00:00

pages

1465-1470

issue

8

eissn

1673-5374

issn

1876-7958

pii

NeuralRegenRes_2018_13_8_1465_235307

journal_volume

13

pub_type

杂志文章

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