WO2008035266A2

WO2008035266A2 - Automatic seed point selection

Info

Publication number: WO2008035266A2
Application number: PCT/IB2007/053730
Authority: WO
Inventors: Thomas Buelow; Rafael Wiemker; Roland Opfer
Original assignee: Koninklijke Philips Electronics N.V.; Philips Intellectual Property & Standards Gmbh
Priority date: 2006-09-21
Filing date: 2007-09-17
Publication date: 2008-03-27
Also published as: WO2008035266A3

Abstract

A computer program to identify a single seed point in an image is presented in which a manually positionable region of interest is presented to the user in the image and a single seed point is selected according to pre-defined criteria from the pixels delineated by the region of interest. Such seed points are used to initialise, for example, segmentation algorithms. The invention improves accuracy of seed point selection and also increases reproducibility. In an advantageous embodiment the region of interest is also sizable and a workstation and computer mouse with rotatable control device are provided, where the rotatable control device is used to control the size of the region of interest.

Description

Automatic seed point selection

FIELD OF THE INVENTION

The invention relates to a computer program to find a single seed point in an image.

Many computer programs, algorithms and sub-routines used in image analysis, particularly medical image analysis, require initialization with a starting point, known commonly as a seed point. The seed point, usually an individual pixel or voxel within the image provides some initial value or values, for example by providing an initial grey value or set of coordinates for the computer program, algorithm or sub-routine.

BACKGROUND OF THE INVENTION

US 2005/0031202 discloses a technique for segmenting a structure of interest within an image, the technique beginning with the step of seed point selection within the structure. The seed point can be identified by the user.

Correct manual identification of a suitable seed point is prone to error. The user may inadvertently select an incorrect pixel, particularly in images with a wide variation in grey value over a small number of contiguous pixels, for example in images with considerable noise. Semi-automatic algorithms which require user identification of the seed point suffer from the same disadvantage, as do fully automatic algorithms which allow user intervention to select a new seed point upon failure of the algorithm.

SUMMARY OF THE INVENTION

It is an object of the invention to provide a computer program to allow more accurate manual selection of a suitable seed point.

This is achieved according to the invention whereby the computer program is arranged to provide a region of interest in the image and further arranged to allow the region of interest to be manually positioned prior to selection of the single seed point, and arranged to automatically select the single seed point according to at least one pre-defined criterion from the pixels delineated by the region of interest. Manual selection of a suitable seed point required for the initiation of an image processing algorithm or a sub-routine is prone to error because of inherent small variations in placement of the cursor on the image. This may have a large effect on the output of the image processing algorithm when, for example, the value of the grey level of the selected seed point is used as an input value for the algorithm and the grey level values vary widely from pixel to pixel over the region in which the suitable seed point can be expected to be situated. In such cases it is found empirically that repeated user selection of seed point for sequential iterations of the algorithm often produce varying output results due to an inherent spread in user defined input seed point selection. The invention removes this source of error by providing the user with a region of interest which is moveable within the image. The user controls the position of the region of interest and is able to translate it within the image until it surrounds the portion of the image in which the user expects a suitable seed point to reside. Once the region of interest is suitably positioned, the seed point is automatically identified within the region of interest according to a single pre-defined criterion or several pre-defined criteria.

In effect, the user places a region of interest instead of placing a seed point. It has been found that it is easier for the user to manually align a region of interest to the portion of the image where a suitable seed point could be expected to reside than it is to try to select the suitable seed point from among the pixels in that portion of the image. A region of interest is inherently larger then the single point identifiable by the cursor and intentional placement is therefore correspondingly easier. The criterion, or criteria, by which the seed point would have been manually selected allow, when translated into a pre-defined criterion, or criteria, the automatic selection of the correct pixel within the postioned region of interest. Thus the correct seed point is more accurately identified. It has been found that a particularly useful embodiment of the invention is a region of interest that can also be altered in size. In this embodiment the user has improved control over the region of interest and can delineate the region of interest around the portion of the image in where a suitable seed point can be expected to reside.

The pixels within the region of interest provided for the user form a connected space.

A particularly useful embodiment has been found to be a region of interest with a substantially circular shape. This may be a completely round circle, but may also be a rounded ellipse. Both have been found to be particularly intuitive shapes for the user to understand and to place over the portion of the image which is suitable for seed point selection. The advantages of the circle embodiment are particularly apparent when the user also has control over the size of the region of interest. A circle whose radius is controllable imparts an impression of zooming towards a single point when the radius is reduced on the screen, and also indicates zooming away from a single point when the radius is increased, and thereby allows the user to gain an understanding of which portion of the image will contain the single seed point, without obscuration behind the cursor.

The region of interest can also take other shapes, for example an ellipse, a square, a rectangle, or even a line. The latter example is particularly advantageous, for example, when a seed point is sought across a section of some object visible in the image, for example an elongated object such as an arterial vessel, a section of bronchus or a section of colon. In this case the user can for example position the line across a suitable width of the object and the seed point is identified from the pixels delineated along the line.

It is important to realize that the eventual single seed point is not merely the point at the center of the region of interest, but is chosen according to a single pre-defined criterion, or several pre-defined criteria, from amongst the group of pixels delineated by the region of interest. Although it is perfectly possible for a pre-defined criterion to in fact be the central point in the region there are many other examples which are clinically found to be advantageous.

In general, the pre-defined criterion, or criteria, for the automatic selection of the seed point are chosen to be those which most suit the application in which the invention is used. The pre-defined criteria are an automation of the required criteria as they would be applied for manual selection of the seed point. So for example, in contrast enhanced images, where any objects of interest might be expected to take up contrast and appear in the resultant image with the subsequently expected range of grey values, the pre-defined criterion could be expected to be selection of the most representative pixel within this range of grey values. To continue the example, if contrast enhanced objects in the image have a high grey value and are subsequently seen to be very bright within the image, a suitable seed point for a segmentation algorithm arranged to segment areas of high contrast would be a pixel which itself has a high, contrast enhanced, grey value. As such, a suitable pre-defined criterion for automatic selection of the seed point within the positioned region of interest would be selection of the pixel with the maximum grey value.

Similarly, selection of the pixels with minimum grey value can also be used. As an alternative example a seed point could be selected by use of a filter. Filters to identify certain attributes within medical images are known, for example 'vesselness' filters, which are sub-routines which search for groups of pixels or voxels representing vessels, usually blood vessels, within an image according to various a priori criteria. Such filters can be used to automatically select a suitable seed point within the region of interest. Similarly, filters sometimes known as 'blobness' filters can be used to identify objects within an image which is characterized by a roundness or 'blob'-like shape. Such filters are highly useful for identifying polyps in colon data sets and lung nodules in lung data sets. Such filters can also be highly advantageously used to automatically select a seed point for use as input value for an image algorithm. In another useful embodiment, a weighting function is applied to the pixels delineated by the region of interest prior to automatic selection of the single seed point. This allows the user to favour automatic seed selection in pre-defined portions of the region of interest. A particularly advantageous embodiment involves use of a weighting function which applies a pixel weight in proportion to the proximity of the pixel to the centre of the region of interest, in other words, one which weights in favour of pixels situated towards the centre of the region of interest. This provides a particularly intuitive embodiment of the invention because it allows automatic selection of the single seed point in the portion of the region of interest which the user recognises as the centre. The user, when he is aware of the criterion or criteria used to automatically select the seed point is empowered to position the region of interest evenly around the portion of the image where he most expects a suitable seed point to reside with confidence that the seed point is more likely to be selected from the pixels in the centre of the region of interest. This embodiment, in effect, allows automatic seed selection to be biased towards the centre of the region of interest. This embodiment is found to be particularly useful in the case when the region of interest has the shape of a circle. The weighting function can be applied directly to the grey values of the pixels or to the filter responses in the case when a filter is applied. One manner in which this can be performed is to multiply the grey value of each pixel by a value dependent on the distance from the position of the pixel to the calculated centre of the region of interest.

A particularly useful weighting function is found to be a Gaussian function centred around the centre of the region of interest. In this case, one manner in which this can be performed is to multiply the grey value of each pixel by a value of the Gaussian function, which value is a function of the distance from the position of the pixel to the calculated centre of the region of interest. The Gaussian values may be further multiplied by a scaling factor to increase or reduce the weighting given to the centre of the region of interest and the rate at which this weight increases.

The skilled person will understand how to arrange a computer program to perform the invention and how to integrate this program into the normal workings of image analysis software.

Although the invention has been described in terms of its application to a two dimensional image it is equally applicable to medical images which show volume renditions. For example, in the case where a two dimensional representation of a three dimensional space is shown the region of interest may take the shape of a two dimensional representation of a sphere.

The invention also concerns a workstation arranged to identify a single seed point in a medical image, and arranged to provide a region of interest in the image and further arranged to allow the region of interest to be manually positioned before selection of the single seed point, and further arranged to automatically select the single seed point according to at least one pre-defined criterion from the pixels delineated by the region of interest. Such a workstation has the advantage that it is arranged to perform the invention.

In a particularly useful embodiment, the workstation is coupled to a computer mouse comprising a rotatable control device, whereby the computer mouse is arranged to provide user control of the region of interest, and further arranged to allow control of the size of the region of interest via the rotatable control device. This arrangement has the advantage that the user can control the position of the region of interest by positioning the mouse, as is known, while controlling the size of the region of interest by use of the rotatable control device.

A suitable rotatable control device is a mouse wheel. The construction of a computer program, its integration into a workstation and the use of the computer mouse with a rotatable control device according to the invention will be clear to the person skilled in the art of medical image processing once he understands how the invention is to work.

BRIEF DESCRIPTION OF THE DRAWINGS

These and other embodiments of the invention will be further explained with the assistance of the Figs.

Fig. 1 shows a workstation suitable for performing the invention. Fig. 2 shows a medical image in which the invention can be used. Fig. 3 shows a region of interest, as used in the invention.

DETAILED DESCRIPTION OF THE EMBODIMENTS

Fig. 1 shows a workstation 101 with a screen 102 on which a medical image 103 is displayed. The image contains various anatomical structures 104 and a region of interest 105 which is moveable within the image. The region of interest 105 can be moved by the mouse 106.

In particularly suitable implementation, the user gains control of the region of interest according to the algorithm in operation and moves the region of interest as though it were a cursor. When the region of interest is situated in the image in such a way that it surrounds the portion of the image in which the user expects a suitable seed point to reside, the user clicks the mouse to allow automatic calculation of the seed point and the initiation of the algorithm which requires the seed point for initialization.

In the particularly advantageous embodiment in which the user also has control of the size of the region of interest the size can be controlled by use of a mouse wheel 107.

Fig. 2 shows a medical image 201 containing an area of tissue 202 which comprises an area of high contrast 203, in other words a recognizable grouping of pixels with high grey values. The contrast medium administered prior to the image acquisition is administered by injection so although the high contrast pixels represent tumor they also represent the blood vessels carrying the contrast agent into the area of tissue 202. A segmentation algorithm arranged to segment the tumor will commonly start from selection of a seed point. A fully automatic seed point selection cannot be used at this point because it requires the output of the segmentation algorithm to differentiate the pixels contained in the tumor from the pixels contained in the blood vessels visible in the image.

Fig. 3 shows the same image 301 containing the area of tissue 302 and the area of high contrast 303. In this case a region of interest 304 has been situated around the area of high contrast 303 by the user. This region of interest 304 can be presented in the image for the user to position and if positioned around the main area of high contrast 303 will allow automatic selection of a seed point lying within the area of high contrast. This seed point will then initialize the segmentation algorithm.

The criterion for automatic seed point selection need not require the same complexity and rigor as the criteria contained within the segmentation algorithm. A simple a priori criterion is sufficient, such as selection of the maximum grey level value when applied to a contrast image.

It can be seen that the invention also allows improved reproducibility. In a case such as that shown in Figs. 2 and 3, the same seed point is highly likely to be automatically selected even if the user places the region of interest in slightly different positions in successive iterations of the segmentation algorithm. In this case the embodiment in which the size as well as the positioning of the region of interest is used is shown to have maximum advantage. Alteration of the size of the region of interest allows the user to balance the size so that it includes the region of interest to be segmented while including as little as possible of the surrounding high contrast blood vessels. Thus it is likely that even with small variations in position the same seed point will be automatically selected.

Although the invention has been described primarily in terms of seed point selection within two dimensional images, one possible application within three dimensional volume imaging can be implemented by presentation to the user of three circular regions of interest in three orthogonal views.

Claims

CLAIMS:

1. A computer program to identify a single seed point in an image, characterized in that the computer program is arranged to provide a region of interest 304 in the image and further arranged to allow the region of interest to be manually positioned prior to selection of the single seed point, and arranged to automatically select the single seed point according to at least one pre-defined criterion from the pixels delineated by the region of interest.

2. A computer program as claimed in claim 1, characterized in that the computer program string is further arranged to allow the region of interest to be manually sized before selection of the single seed point.

3. A computer program as claimed in either claims 1 or 2, characterized in that the pixels in the region of interest form a connected space.

4. A computer program as claimed in any of the previous claims, characterized in that the region of interest has a substantially circular shape.

5. A computer program as claimed in any of claims 1 to 4, characterized in that the pre-defined criterion is selection of the pixel with the maximal grey value from amongst the pixels delineated by the region of interest.

6. A computer program as claimed in any of claims 1 to 4, characterized in that the pre-defined criterion is selection of the pixel with the minimal grey value from amongst the pixels delineated by the region of interest.

7. A computer program as claimed in any of claims 1 to 4, characterized in that the pre-defined criterion comprises use of a filter.

8. A computer program as claimed in claim 7, characterized in that the filter is arranged to identify portions of the image which represent anatomical vessels.

9. A computer program as claimed in any of the previous claims, characterised in that a weighting function is applied to the pixels delineated by the region of interest prior to automatic selection of the single seed point.

10. A computer program as claimed in claim 9, characterised in that the weighting function applies a pixel weight in proportion to the proximity of the pixel to the centre of the region of interest.

11. A computer program as claimed in claim 10, characterised in that the weighting function is a Gaussian function.

12. A workstation 101 arranged to identify a single seed point in a medical image 103, characterized in that it is arranged to provide a region of interest 105 in the image and further arranged to allow the region of interest to be manually positioned prior to selection of the single seed point, and arranged to automatically select the single seed point according to at least one pre-defined criterion from the pixels delineated by the region of interest 105.

13. A workstation as claimed in claim 12, characterized in that it is coupled to a computer mouse 106 comprising a rotatable control device 107, the computer mouse 106 arranged to provide user control of the region of interest, and further arranged to allow control of the size of the region of interest via the rotatable control device 107.

14. method to identify a single seed point in an image 301 characterised in that a positionable region of interest 304 is provided in the image 301 and is positioned in the image 301 prior to selection of the single seed point, and further that the single seed point is selected according to at least one pre-defined criterion from the pixels delineated by the region of interest 304.