The following is a description of the measurement software and options available on the UCL image analysis system; however all these techniques apply equally to other image analysis systems:
A sample of the filamentous microorganism is fixed to a microscope slide and dyed. The slide is placed under a microscope and, using a television camera mounted on the microscope, a video picture is passed to a computer capable of image processing and analysis.
Initial work on image analysis of filamentous microorganisms used supplied software and required
considerable manual intervention. Although the method used by Adams and Thomas has been shown to be more accurate and considerably quicker than the digitising
method, it is clear that the image analysis system can only show its full potential by additional automation. This complete automation required development of application- specific software, such software has been written by Packer and Thomas . This morphological characterisation
program was designed to be highly flexible; running
automatically but with manual options at various intervals throughout. The basic algorithm of the program is shown in figure 8 ; this shows the optional editors for manual intervention. The program has three main phases:
a) Setting-up.
b) Image processing. c ) Measurement.
The setting-up phase involves inputting parameters that are needed for each running of the program. As described previously, the sizing calibration is achieved using a graticule scale. Next, an active measuring frame must be established; this is a boundary which prevents objects, at the edge of the image, from being truncated and causing inaccurate results. The width of this boundary must be greater than the longest microorganism to be
C hapter 1: Introduction. F I E L D O F V I E W ► IMAGE C A P T U R E
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S E G M E N T A T I O N1
R E M O V A L O F F A L S E O B J E C T S ^ Initial e d i t o r T U S E O F G U A R D R E G I O Ni
S K E L E T O N I S A T I O N --- ^ s k e l e t o n e d i t o r u n m e a s u r a b l e " --- I M A G E S P L I T m e a s u r a b I e u n m e a s u r a b I es e d i t o r IMAGE S P L I T m e a s u r a b I e u n m e a s u r a b I e re cl a ss if i ca ti o n editor " M E A S U R E M E N S O R A B O R T N E W F I E L D OF V IEW D A T A A N A L Y S I Sframe are only considered significant if their lowest hyphal tip is in the frame. The program drives an
automatic microscope stage and the motion of this stage is set for abutting measuring frames in two directions, giving complete coverage of any region of interest. Finally, some parameters involved with image processing are set, and options for the level of manual editing are chosen.
Once the image has been captured, the image processing begins with segmentation. Then the binary image must be cleared of false objects, for example, media particles and dust. This is achieved by the use of a preset circularity parameter. This has a maximum value of unity for a
perfect circle and decreases with increasing departure from circularity. Hence the long fibres of the filamentous microorganisms have a low value. Objects with a
circularity value higher than the preset value (those objects which are too circular) are removed.
The objects remaining should all be microorganisms; these are skeletonised, that is, the pixels medial between the edges of the object are found, outlining skeletons for analysis. Noise spikes are often formed during this
process, this may be due to media debris or an artefact of the skeletonisation process. Noise spikes of lengths less than a preset number of pixels are removed from the
skeletons to prevent the software from treating them as b r a n c h e s .
The binary skeleton images are divided into two
groups; measurable microorganisms and clumped (aggregated) material. Clumps are distinguished because they contain loops or holes, for the purpose of image analysis this means regions of background enclosed within the object. Objects in each of these two groups are analysed
separately.
As mentioned above, the processing phase has a number of optional manual editors available. These can be
selected during setting-up if appropriate. In some instances a fully automated system can mis-classify an object, editing allows any such error to be corrected, but
C hapter 1: Introduction.
it significantly slows processing and makes the process much more labour intensive. Within the editing option the
following procedures are available:
Accept - select objects of interest and reject the remainder.
Reject - reject uninteresting objects and the select remainder.
Fill - fill an object (with foreground colour) to prevent it being classified as a clump.
Draw - draw on additions to an object to give a more accurate representation.
Erase - as above, but removing a section of an object. Kill - cancel all editing.
In the measurement phase both field and object measurements are taken:
Field measurements are ones in which the
contribution of each object is not individually known or recorded, but information recorded at pixel level is merely summed to provide a single measurement for the entire view.
By taking a total pixel count of both images, the proportion of unmeasurable (clumped) and measurable material can be estimated.
Object measurements, as the name implies, are
measurements on each individual object. The objects can then be classified by their individual measurements. For each measurable microorganism the longest connected path through the object is found. This is considered to be the main hypha and its length is estimated using the sum of the inter-pixel distances . This hypha is then erased from the image, and the next longest connected path is found. By this recursive algorithm each branch and sub-branch of a microorganism is found and measured. Total hyphal length, number of tips and length of hyphal growth unit are
calculated. The results are passed to a data file for subsequent statistical analysis using proprietary software.
As far as image analysis is concerned, clumping of the microorganisms can create measurement problems, but in this investigation this was not found to be a problem since
clumping did not occur with any of the microorganisms used in this work.
1.3 Rheology.
Rheology is defined as the study of the flow and deformation of matter. It is the science concerned with the mechanics of deforming bodies .
Rheologists apply methods for the measurement of
rheological properties; these are methods for establishing the relationship between stress, strain and time for some test material.