GC Image Users' Guide

Image Processing

Image processing filters typically are required to correct acquisition artifacts. This chapter describes three image processing filters:

A preliminary step in GCxGC image processing is to optionally shift the phase of the image with respect to the start time of the second dimension. In GC Image, this is termed Shift Phase.
Removing the baseline (or background) level introduced by the system is an important step in precise quantification. In GC Image, this is termed Correct Baseline.
GC Image provides for point-wise Arithmetic Operations, which operate on a pixel-by-pixel basis, with either scalar values or images.

Shift Phase, Correct Baseline, and Arithmetic Operations are invoked through the Filter menu of the Image Viewer and via buttons on the Image Viewer tool bar. Several other operations available from the Filter menu of the Image Viewer are described in other chapters. Detect Blobs is described in the next chapter Detection and Analysis. Load Template, Match Template, and Apply Template are described in the chapter Pattern Recognition. Search Library is described in chapter GCxGC-MS Data.

Shift Phase

A GCxGC image is created from a time-ordered stream of samples. Ideally, the maximum time required for each second column separation is less than the time period of the thermal modulation. Maintaining this condition across the whole of the GCxGC process requires proper temperature programming. Then, all of the samples of each second column separation are contained in a single column of the image.

Under these conditions, it is desirable to synchronize the time zero of the second column separations to the row zero of the image. However, depending on temporal relationship between the start of sampling and the thermal modulation period, post-acquisition phase shifting of the data may be required. Even if sampling and thermal modulation are synchronized, other variations can make shifting phase desirable.

As an example of the need for phase shifting, suppose that in one data set, sampling is initiated at the time of the start of the thermal modulation cycle (as in Figure 1.A below) and that in another data set, sampling is initiated at the time just before the start of the thermal modulation cycle (as in Figure 1.B below). If this is the only difference in data acquisition, then the peaks in the second image will be offset relative to the first image.

In this case, the phase could be aligned by padding one of the images so that the modulation period was consistent with respect to the columns of both images. Padding is required only in the first column at the beginning of the image. Then, the first column, which contains the padding, is excluded from analysis, as is the partial column shifted off the last column at the end of the image. An example of this phase shift operation is illustrated in Figure 1.C.

Figure 1.A: The start of sampling is synchronized with the start of the modulation cycle.

Figure 1.B: The start of sampling is not synchronized with the start of the modulation cycle.

Figure 1.C: The image columns from the unsynchronized image are brought back in alignment by padding the data.

In GC Image, the Shift Phase operation is invoked by either clicking the Shift Phase button on the Image Viewer tool bar or selecting the Shift Phase item from the Filter menu. The operation begins with a popup dialog box for entering the number of pixels to be shifted. The shift can be a positive or negative number for an upward or downward shift, respectively. The actual shift is set to the number of pixels specified by the user modulo the number of pixels in the second column separation. The interface also supports resetting to the original phase.

Figure 2.A illustrates an image before Shift Phase. The color scale is mapped over a narrow range to make the small blobs at the top and bottom of the image more visible. Note that some blobs wraparound to the bottom of the image. Figure 2.B shows the image after Shift Phase of -75 pixels. The blobs that were wrapped around to the bottom of the image are shifted back to the top of the image.

Figure 2.A: An image before Shift Phase has wraparound.

Figure 2.B: An image after Shift Phase corrects wraparound.

Correct Baseline

In gas chromatography, the signal peaks, which correspond to chemical constituents in the sample, rise above a baseline level in the output. Under controlled conditions, the baseline level consists primarily of the steady-state standing-current baseline in standard GC detectors and temperature-induced column-bleed which causes a rise in the signal in the later portions of temperature-programmed runs. Accurate quantification of the chemical-related peaks requires subtraction of the baseline level from the signal.

Figure 3 illustrates a perspective plot of an isolated peak rising to a maximum value of over 23 pico-amps. However, the baseline in that region of the image is more than 14 pico-amps, so the actual maximum peak height induced by the sample chemical is less than 10 pico-amps.

Figure 3: Perspective plot of a GCxGC sub-image containing an isolated blob peak.

In a simple model of the two-dimensional GC process, each image pixel produced by the system is the sum of:

A non-negative baseline offset value that is present even when there is no sample compound detected.
The signal due to the presence of the detected sample compound(s).
Random noise fluctuations (including quantization).

Under typical controlled conditions, the baseline offset values change relatively slowly over time, forming a slightly curving baseline across the image. The signal and noise fluctuate more rapidly over time and so can be separated from the slowly varying baseline offset.

The GC Image Correct Baseline operation estimates the baseline across the chromatographic image based on a few structural and statistical properties of the two-dimensional chromatographic process. Then, the baseline is subtracted from the image, producing a chromatograph in which the peaks rise above a zero-mean baseline level. (The noise is assumed to be zero-mean, in that any offset in the image is modeled in the baseline.)

To perform the Correct Baseline operation, either click the Correct Baseline button on the Image Viewer tool bar or select the Correct Baseline item from the Filter menu. The correction operation takes a brief time (typically no more than a few seconds), after which the current image is altered. After baseline correction, it may be desirable to re-colorize the image to reflect the new range of values. For details about this process, see "Background Removal and Peak Detection in Two-Dimensional Gas Chromatography", Reichenbach, Ni, Zhang, and Ledford, Journal of Chromatography A, 985(1-2):47-56, 2002.

Configure->Configure Settings on the Image Viewer menu bar provides four parametric values for Baseline Correction:

The algorithm divides the image into successive strides, with the assumption that in each stride there will be a deadband (a region where there are no sample eluents and the pixel values are determined by the baseline value and noise). One of the configurable parameters is the size of the stride. The stride can be set to 0.5 (meaning the stride is half the size of the second column dimension, under the assumption that there is a deadband in both halves of each second column separation) or to 1.0 (meaning the stride is equal to the second column dimension, under the assumption that there is a deadband in each second column separation). The default is 1.0. A larger stride size tends to produce an estimate of the baseline that is smaller valued.
The algorithm looks for a number of the smallest pixels in each stride, under the assumption that the smallest pixels are most probably in the deadband. The number of smallest pixels selected in each stride is one of the configurable parameters. The default number of deadband pixels expected in each stride is 5 and the minimum number is 3. A larger number of smallest pixels tends to produce an estimate of the baseline that is larger valued.
The algorithm performs some smoothing of its estimate of the baseline. The size of the filter window used for smoothing is a configurable parameter. The default size parameter for smoothing is 7 and the minimum size is 3. A larger size parameter for smoothing tends to produce an estimate of the baseline that is more slowly changing.
The algorithm estimates the expected range of baseline values plus noise using a configurable parameter of the ratio of the size of the range to the estimated standard deviation of the noise. The default ratio is a range that is 3.5 times the noise standard deviation. Note, after more testing the default may be increased. The minimum ratio is 1.0. A larger ratio tends to produce an estimate of the baseline that is larger valued.

Figure 4.A illustrates an image before baseline correction. The image is for a blank run (i.e., no sample) and the value range of the color map is set to be very small (13 picoamps to 15 picoamps) in order to highlight the small but clear increase in baseline value with time. Figure 4.B illustrates the same image after Correct Baseline (with a value range of -1 to 1). The rise in the baseline level has been removed. Note that baseline correction does not remove more quickly varying acquisition artifacts.

Figure 4.A: An image before Correct Baseline has a clear increase in baseline level from left to right.

Figure 4.B: An image after Correct Baseline corrects the baseline level.

Arithmetic Operations

GC Image provides for point-wise Arithmetic Operations, which operate on a pixel-by-pixel basis. The currently supported operations are addition, subtraction, and multiplication. The operands are the current image and either a scalar value applied to all pixels or a GC Image file specified by its filename. If a second image is specified, it must have the same size in pixels as the current image. The Arithmetic Operations popup is shown in Figure 5.

Figure 5: The Arithmetic Operations popup.

Point-wise subtraction of a so-called blank run (a chromatographic run with no sample input) can be used to remove background artifacts. Point-wise addition of images can be used to obtain an average chromatogram.

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