First, sectioning the surface of the block introduces unavoidable distortions onto the surface.
FOCALPOINT 2 SERIAL SERIAL
While less labor intensive than serial section analysis there are several limitations. This process is then repeated throughout the tissue volume at fixed increments to achieve whole organ imaging. In block-face imaging, the surface of the tissue block is removed using a microtome and the newly exposed tissue surface is imaged (Ewald et al., 2002 Denk and Horstmann, 2004). To circumvent some of the limitations imposed by serial section analysis, block-face approaches have been developed. Furthermore, as this process is performed manually, the large datasets, required to generate robust and conclusive data, pose challenges both in terms of the labor and cost involved.
FOCALPOINT 2 SERIAL FULL
However, as this method requires that tissue samples be sectioned prior to imaging, irreducible distortions are introduced into the tissue sections that preclude accurate full 3D reconstructions of the tissue. For studies attempting to construct a 3D representation of the original tissue, the individually imaged sections must be aligned and digitally reassembled. In this technique, a tissue is manually sectioned into thin slices on a cryostat before the tissue section is mounted onto a microscope slide, stained and imaged using a microscope. Traditionally, these studies have relied upon serial section analysis to investigate 3D cytoarchitecture of the CNS. The three dimensional (3D) structure of the CNS (Bourdenx et al., 2014) is critical for proper network formation and function and therefore has been intensely studied. The combination of advances in these three disciplines have a sum greater than the individual parts and particularly benefit the field of neuroscience, where researchers studying the central nervous system (CNS) are attempting to decipher a complex and enormous 3D network of interconnected neural circuits and cell types. Each of these fields address an important aspect of quantitative biological imaging: optical microscopy methods visualize tissues and map the spatial-temporal relationship between components too small to be seen by the naked eye tissue labeling techniques establish contrast and biochemical specificity of tissue components computer-aided image analyses quantitatively explore relationships between the various components and makes it possible to handle the vast amounts of data that is generated (Klunk et al., 2002 Dean and Palmer, 2014 Piccinini and Shagrir, 2014 Jordan and Mitchell, 2015 Feng et al., 2015). Over the last two decades there have been dramatic improvements in the fields of microscopy, tissue labeling, and computational image analysis.
0 kommentar(er)
