高分翻译一段英文~~~急求，在线等

高分翻译一段论文内容，英译汉 【不要机器翻译】，要通顺、精准一点的
在线等~~~~~~~~~急急急~~~~~~~~感激不尽
注：文中标题和括号里的数字要保持原位，不要修改，是关于认知神经研究技术方面的~
The HBP-funded Internet Brain Segmentation Repository(37) is developing a

repository of segmented brain images to use in comparing these different

methods.
Popular segmentation and reconstruction techniques include reconstruction

from serial sections,region-based methods,edge-based methods,model or

knowledge-based methods,and combined methods.

2.2.1 Reconstruction from Serial Sections
The classic approach to extracting anatomy is to manually or semi-

automatically trace the contours of structures of interest on each of a

series of aligned image slices,then to "tile"a surface over the contours

(38).The tiled surface usually consists of an array of 3-D points connected

to each other by edges to form triangular facets.The resulting 3-D surface

mesh is then in a form where it can be further analyzed or displayed using

standard 3-D surface rendering techniques(39).
Neither fully automatic contour tracing nor fully automatic tiling has

been satisfactorily demonstrated in the general case.Thus,semi-automatic

contour tracing followed by semi-automatic tiling remains the most common

method for reconstruction from serial sections,and reconstruction from

serial sections itself remains the method of choice for extracting

microscopic 3-D brain anatomy(18).

2.2.2 Region-Based and Edge-Based Segmentation
This and the following sections primarily concentrate on segmentation at the macroscopic level.
In region-based segmentation voxels are grouped into contiguous regions

based on characteristics such as intensity ranges and similarity to their

neighbors(40).A common initial approach to region-based segmentation is

first to classify voxels into a small number of tissue classes such as gray

matter,white matter,cerebrospinal fluid and background then to use these

classifications as a basis for further segmentation(41,42)