In lieu of an abstract, here is a brief excerpt of the content:

13 Microscopic Slice Image Processing and Automatic Labeling A supervised interpretation of the initial data analysis model from section 4.1 leads to a classification problem: given a set of input-output samples, find a map that interpolates these samples, and, hopefully generalizes well to new input samples. Such a map thus serves as classifier if the output consists of discrete labels. Classification based on support vector machines [36, 37, 229] or neural networks [111] has prominent applications in biomedical data analysis. Here we review an application to biomedical image processing [260]. While many different tissues of the mammalian organism are capable of renewing themselves after damage, it was long believed that the nervous system is not able to regenerate at all. Nevertheless, the first data showing, that the generation of new nerve cells in the adult brain could happen were presented in the 1960s [7], showing new neurons in the brain of adult rats. In order to quantify neurogenesis in animals, newborn cells are labeled with specific markers such as BrdU; in brain sections these cells can later be analyzed and counted through the use of a confocal microscope. However, so far this counting process had been performed manually. The goal of this chapter is to automate the task of counting labeled cells, which is currently done manually in many laboratories. Our novel algorithm contributes to a substantial speed-up in experimental settings. Furthermore, when comparing manual counts, differences in the counts are often noticed; hence, with an automated counting algorithm we hope to achieve an objective counter with known error bounds. The chapter is organized as follows: section 13.1 presents the necessary neurobiological background of the analyzed section images. We then give an overview of the ZANE cell-counting algorithm in section 13.2. Section 13.3 presents an efficient algorithm for image stitching used in ZANE to allow for counting larger brain sections. The neural-network cell classifier is constructed in section 13.4, and is then used to analyze cell images in section 13.5. Comparisons with other methods are presented in section 13.6, and our main results are shown in section 13.7, comparing ZANE with manually counted section images. We finish with a discussion of further applications and future work in section 13.8. 350 Chapter 13 13.1 Biological background While many different tissues of the mammalian organism are capable of renewing themselves after damage, it was long believed that the nervous system is not able to regenerate at all. The first data showing that new nerve cells could be generated in the adult brain could happen were presented by Altman and Das in the 1960s. They published histological data showing new neurons in the brain of adult rats [7]. To identify those cells, they used the audioradiographic method by labeling newly emerged cells with 3H-thymidine. As there were no tools available for proving that these cells were adult nerve cells, their findings remained relatively unnoticed. In the early 1980s S. Goldman and F. Nottebohm found newly developed neurons in the dorsomedial striatum of adult songbirds [94]. But adult neurogenesis did not come into focus until the 1990s [16, 40, 146], when new techniques to analyze the newborn neurons were established. In particular, the introduction of thymidine-analogon bromodeoxyuridine (BrdU) as a nonradioactive marker for dividing cells gave rise to many new studies concerning adult neurogenesis. On the other hand, by establishing confocal microscopy it became possible to identify the characteristics of the newborn cells more clearly. After that it could be shown that adult neurogenesis occurred in rodents (rats and mice), but also was found in primates and even in humans [40, 72, 75]. But neuroscientists also found that under physiological conditions adult neurogenesis is restricted to two brain regions. One is the lateral wall of the lateral ventricle, which is called the subventricular zone. The cells generated there migrate through the rostral migratory stream to the olfactory bulb, where they differentiate into mature neurons. The other “neurogenic” region in the adult brain is the granular cell layer of the dentate gyrus in the hippocampal formation of the temporal lobe. There, new cells are born in a thin zone right below the granular cell layer. During differentiation the cells integrate into the granular cell layer and become mature neurons with all functions of a granular cell [274]. “Neurogenesis” does not mean proliferation of cells alone; these newborn cells...

Share