43 lines
6.1 KiB
Markdown
43 lines
6.1 KiB
Markdown
---
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title: "Bioimage informatics"
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chunk: 2/2
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source: "https://en.wikipedia.org/wiki/Bioimage_informatics"
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category: "reference"
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tags: "science, encyclopedia"
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date_saved: "2026-05-05T14:01:33.460591+00:00"
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instance: "kb-cron"
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---
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Segmentation of cells is an important sub-problem in many of the fields below (and sometimes useful on its own if the goal is only to obtain a cell count in a viability assay). The goal is to identify the boundaries of cells in a multi-cell image. This allows for processing each cell individually to measure parameters. In 3D data, segmentation must be performed in 3D space.
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As the imaging of a nuclear marker is common across many images, a widely used protocol is to segment the nuclei. This can be useful by itself if nuclear measurements are needed or it can serve to seed a watershed which extends the segmentation to the whole image.
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All major segmentation methods have been reported on cell images, from simple thresholding to level set methods. Because there are multiple image modalities and different cell types, each of which implies different tradeoffs, there is no single accepted solution for this problem.
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Cell image segmentation as an important procedure is often used to study gene expression and colocalization relationship etc. of individual cells. In such cases of single-cell analysis it is often needed to uniquely determine the identities of cells while segmenting the cells. Such a recognition task is often non-trivial computationally. For model organisms such as C. elegans that have well-defined cell lineages, it is possible to explicitly recognize the cell identities via image analysis, by combining both image segmentation and pattern recognition methods. Simultaneous segmentation and recognition of cells has also been proposed as a more accurate solution for this problem when an "atlas" or other prior information of cells is available. Since gene expression at single cell resolution can be obtained using these types of imaging based approaches, it is possible to combine these methods with other single cell gene expression quantification methods such as RNAseq.
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=== Tracking ===
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Tracking is another traditional image processing problem which appears in bioimage informatics. The problem is to relate objects that appear in subsequent frames of a film. As with segmentation, the problem can be posed in both two- and three-dimensional forms.
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In the case of fluorescent imaging, tracking must often be performed on very low contrast images. As obtaining high contrast is done by shining more light which damages the sample and destroys the dye, illumination is kept at a minimum. It is often useful to think of a photon budget: the number of photons that can be used for imaging before the damage to the sample is so great that data can no longer be trusted. Therefore, if high contrast images are to be obtained, then only a few frames can be used; while for long movies, each frame will be of very low contrast.
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=== Registration ===
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When image data samples of different natures, such as those corresponding to different labeling methods, different individuals, samples at different time points, etc. are considered, images often need to be registered for better comparison. One example is as time-course data is collected, images in subsequent frames must often be registered so that minor shifts in the camera position can be corrected for. Another example is that when many images of a model animal (e.g. C. elegans or Drosophila brain or a mouse brain) are collected, there is often a substantial need to register these images to compare their patterns (e.g. those correspond to the same or different neuron population, those share or differ in the gene expression, etc.).
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Medical image registration software packages were early attempts to be used for the microscopic image registration applications. However, due to the often much larger image file size and a much bigger number of specimens in the experiments, in many cases it is needed to develop new 3D image registration software.BrainAligner is software that has been used to automate the 3D deformable and nonlinear registration process using a reliable-landmark-matching strategy. It has been primarily used to generate more than 50,000 3D standardized fruitfly brain images at Janelia Farm of HHMI, with other applications including dragonfly and mice.
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== Important Venues ==
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A consortium of scientists from universities and research institutes have organized annual meetings on bioimage informatics since 2005. The ISMB conference has had a Bioimaging & Data Visualization track since 2010. The journal Bioinformatics also introduced a Bioimage Informatics track in 2012. The OpenAccess journal BMC Bioinformatics has a section devoted to bioimage analysis, visualization and related applications. Other computational biology and bioinformatics journals also regularly publish bioimage informatics work. A European Union Cost action called NEUBIAS (network of european bioimage analysts) has been organizing annual conferences as well as bioimage analyst training schools and taggathons since 2017.
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== Software ==
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There are several packages that make bioimage informatics methods available through a graphical user interface such as ImageJ, FIJI, CellProfiler or Icy. Visualization and analysis platforms such as Vaa3D have appeared in recent years and have been used in both large scale projects especially for neuroscience and desktop applications.
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Other researchers develop their own methods, typically based on a programming language with good computer vision support such as Python, C++, or MATLAB. The Mahotas library for Python is one popular example. Although, examples of researcher developed methods in programming languages with less computer vision support as R exist (e.g. trackdem ).
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== See also ==
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Focus stacking The technique of combining multiple images with difference focus distances into one.
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High-content screening
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digital pathology
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Medical imaging
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== External links ==
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Vaa3D: High-performance multi-dimensional image visualization and analysis
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Bioformats The Image file IO engine that supports dozens of formats
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== References == |