X-ray or gamma ray systems or devices – Specific application – Computerized tomography
Reexamination Certificate
2000-10-06
2001-11-27
Kim, Robert H. (Department: 2882)
X-ray or gamma ray systems or devices
Specific application
Computerized tomography
C378S004000, C378S020000, C378S086000, C378S089000
Reexamination Certificate
active
06324248
ABSTRACT:
The invention relates to a method of deriving a cross-sectional distribution of density values from an object data set of data values, wherein
the object data set associates data values with positions in three dimensions and represents an object,
the cross-sectional distribution associates density values with positions in a cutting plane, and
the cross-sectional distribution represents a cross-section along the cutting plane through the three-dimensional object.
The invention also relates to a computed tomography device.
A method and a computed tomography device of this kind are known from German Offenlegungsschrift DE 195 41 500.
The known computed tomography device includes an X-ray source and an X-ray detector which can rotate together about the object to be examined. Using the known method, the known computed tomography device acquires a plurality of cross-sectional images of the object along mutually parallel planes having a predetermined orientation. The cross-sectional images are acquired notably along a number of mutually parallel planes. This is achieved by rotating the X-ray source and the X-ray detector about the object while displacing the object and the X-ray detector and the X-ray source relative to one another. It is thus achieved that a cross-sectional image is acquired each time along the plane in which the X-ray detector and the X-ray source rotate about the object. Subsequently, the X-ray source with the X-ray detector and the object are displaced relative to one another, so that the plane in which the X-ray source and the X-ray detector rotate about the object is shifted and a next cross-sectional image is acquired. The cross-sectional images correspond to the data set and relate to a (sub-)volume of the object. An additional cross-sectional image is derived from the cross-sectional images. The additional cross-sectional image represents a cross-section through the object which has an orientation and a position within the object which can be chosen at random. The additional cross-sectional image constitutes the cross-sectional distribution. According to the known method, each time when a next cross-sectional image is acquired, the line of intersection of the plane along which the current cross-sectional image is acquired with the selected plane of the additional cross-sectional image is determined. The brightness values of the currently acquired cross-sectional image in positions on the relevant line of intersection are used as brightness values of the additional cross-sectional image. Thus, the additional cross-sectional image is composed “on-the-fly” during the acquisition of the cross-sectional images.
It is a drawback of the known method that the spatial resolution of the additional cross-sectional image differs in the directions perpendicular to and in the plane along which the cross-sectional images are acquired. Because of this direction-dependent spatial resolution, the diagnostic quality of the additional cross-sectional image is not very good.
It is an object of the invention to provide a method of deriving from the object data set a cross-sectional image which, in comparison with the result obtained by means of the known method, is a more faithful rendition of the cross-section of the object along the cutting plane.
This object is achieved by means of a method according to the invention which is characterized in that data values of the object data set in positions near and outside the cutting plane are used to calculate density values of the cross-sectional distribution.
The method according to the invention is advantageously used for forming a cross-section of a spatial object along the cutting plane from data values of the spatial object. The cross-section generally relates to a part of the interior of the object which is of importance for the examination of the object. The method utilizes an object data set of data values relating to the object. Such data values may relate to a variety of properties of the object, such as the spatial density distribution of the materials encountered in the object. Other examples in this respect are the temperature within the object, the magnetization, the electrical polarization in the object or the local elasticity of the object. The cross-section derived from the object data set by means of the method is represented by the cross-sectional distribution of density values. These density values represent the distribution along the cutting plane of the property of the object as represented by the data values.
In order to examine the interior of the object, there is determined, for example by selection, a cutting plane along which the cross-section through the object is taken. Such a cutting plane is often a flat surface through the object. It is alternatively possible to take a curved surface through the object as the cutting plane. The invention can even be suitably used for a cutting plane which extends through the object in a complex manner. The cross-sectional distribution associates density values with positions in the cutting plane. Such a position in the cutting plane usually does not coincide with a position in which a data value of the object data set is available. This is because the object data set is often constituted by data values on a three-dimensional grid. For example, a cubic grid is used. The cutting plane usually extends between the grid points of the grid of the object data set. According to the invention nearby positions with individual data values of the object data set are identified for a position in the cutting plane for which a density value is required. Notably positions outside the cutting plane are thus also identified. The density value in the relevant position in the cutting plane is calculated on the basis of the data values associated with said identified positions. Density values can thus be calculated for any desired position in the cutting plane. In a position in the cutting plane with which a data value has already been associated by the object data set, this data value can also be used to calculate the density value of the cross-sectional distribution in the relevant position. This situation occurs at the points of intersection of the cutting plane and the grid of the object data set. The density value in the relevant position in the cutting plane can be calculated from the data values of the data set in a variety of ways. A very simple calculation consists, for example, in identifying for the relevant position in the cutting plane the nearest position with a data value of the object data set and in taking this data value as the density value. Another very simple calculation is, for example, to take the data value with the maximum or minimum value of the object data set as the density value for individual positions in the cutting plane in a predetermined direction, for example perpendicular to the cutting plane and within a maximum distance from the cutting plane. This comes down to a maximum (or minimum) intensity projection (MIP and mIP, respectively) over an effective slice thickness. Accurate results are obtained for the density values of the cross-sectional distribution by, for example linear or non-linear interpolation of a plurality of data values of the object data set in positions in the vicinity of (or possibly in) the relevant positions in the cutting plane.
These and other aspects of the invention will be elaborated hereinafter on the basis of the following embodiments which are defined in the dependent Claims.
Particularly accurate results are obtained for the density values by basing the calculation of the individual density values on data values of the object data set which are associated with individual positions in the cutting plane to both sides of the cutting plane. It as been found that a faithful representation of the cross-section through the object is thus obtained.
Notably details of low contrast are thus clearly visualized in a rendition of the cross-sectional distribution. Such a rendition is, for example an image on a screen, such as a liquid crys
Timmer Jan
Wilting Jantje Edith
Hobden Pamela R.
Kim Robert H.
U.S. Philips Corporation
Vodopia John
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