2012
DOI: 10.3414/me11-02-0038 View full text |Buy / Rent full text
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Abstract: The proposed simple and label free adaptive variant might be the method of choice when it comes to autonomous cell farming. Hereby, it is essential to have reliable and unsupervised mitosis detection that covers all phases of cell growth.

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“…Active contour methods have been successfully used to trace cells [36,37], cellular components [38] and animals [37], in high-contrast images, but because these methods search for compartment boundaries, they are less useful in noisy, low-contrast images and situations where cells often change direction [37]. Another commonly used segmentation method is a noise threshold, in which a specific intensity value is chosen and all intensities falling below this threshold value are deemed background noise [39,40]. There is often high variability in cell fluorescence, however, which can render thresholding methods ineffective.…”
Section: Introductionmentioning
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“…Active contour methods have been successfully used to trace cells [36,37], cellular components [38] and animals [37], in high-contrast images, but because these methods search for compartment boundaries, they are less useful in noisy, low-contrast images and situations where cells often change direction [37]. Another commonly used segmentation method is a noise threshold, in which a specific intensity value is chosen and all intensities falling below this threshold value are deemed background noise [39,40]. There is often high variability in cell fluorescence, however, which can render thresholding methods ineffective.…”
Section: Introductionmentioning
“…The open source toolkit MITK-DI provides a comprehensive software framework for model-based analysis and interactive data exploration of diffusion MR images. In the last contribution of this focus theme, the use of models in the field of microscopic cell image analysis is illustrated [16]. Morphological features are extracted and analyzed automatically with the goal to detect adaptive mitosis of in vitro stem cell tracking data.…”
Section: Resultsmentioning
“…In the focus theme new approaches for the model-based segmentation and analysis of dual-energy CT images [9], radiographic images [10], time-of-flight, phasecontrast and diffusion MR images [11][12][13][14][15] as well as microscopic cell images [16] are presented as examples of the development in this challenging field.…”
Section: Discussionmentioning
“…However, available software fails to automatically detect and quantify high axon numbers and the morphological features of AxD (swellings and fragments). The reason may be two-fold: 1) Available software relies on image binarization 14,15 , which can lead to information loss and low sensitivity as thin axons may not be recognized. 2) The analysis requires subjective and time-consuming manual annotations, e.g., thresholding and defining the region of interest [16][17][18] .…”
Section: Introductionmentioning