1. Field of the Invention
An object of the present invention is a method for the processing of the image of a batch of images, particularly a batch of images obtained by means of a gamma camera. The invention may, however, be applied to images obtained with other medical protocols and, possibly, even images obtained by direct display with a standard type of camera. The processing of the images in the invention preferably relates to the processing of digitized images, namely images whose pixels, which have a given resolution in the image, are assigned image signals that are assessed digitally, most usually in binary mode. The invention relates more particularly to batches of images pertaining to periodic phenomena. A periodic phenomenon may be a phenomenon that evolves in time such as for example heart beats, or it may be a static phenomenon but one that is observed from a viewpoint that periodically returns to the same place.
2. Description of the Prior Art
The essential problem that is sought to be resolved in image processing is that of the elimination of noise. Noise is particularly appreciable in the acquisition of scintigraphic images with gamma cameras. Indeed, the principle of these instruments lies in the counting, for each pixel of the image, of the number of occurrences of radioactive transmissions coming from a particular place in an examined body and corresponding to this pixel in the image. The principle of these instruments is described in the American patent application by Anger, No. 3.011,057. In the field of heart monitoring by gamma cameras, it is customary to make images whose resolution is of the order of 64.times.64 pixels to 128.times.128 pixels. For each pixel, it is possible to accumulate up to 32,000 occurrences or strokes. The number of strokes accumulated for each place is directly proportional to the total period of acquisition of the image.
It can be shown that the influence of the noise in a scintigraphic image decreases with the number of strokes counted for each pixel. For example, the signal-to-noise ratio evolves as the square root of the average number of strokes counted. The tradeoff, however, is that an excessively large number of strokes counted leads to an image being acquired at excessively low speed. The problem arises essentially for the acquisitions of periodic phenomena, especially those pertaining to the functioning of the heart, for which it is sought to obtain images of this organ in different states of its motion. For example, it is habitual to split up the motions of the heart (whose beat is about 1 second) into sixteen successive images pertaining to each of these states.
The estimates given in the present description are presented solely in order to clarify the picture, and can in no way lead to restricting the field of protection of the invention to values within the ranges indicated.
Given the fleeting character of each of the sixteen states of the heart during its period and given the duration needed to acquire a high-quality image (generally 30 seconds), it is necessary to resort to a technique of synchronization during which the strokes counted are assigned, at a given instant, to the image of the state of the heart corresponding to a state identified temporally with respect to a date of synchronization. Thus, sixteen states are identified and, gradually, sixteen images are formed by the accumulation, respectively in each of these images, of the strokes counted out during the corresponding periods. The problem is clearly even more complex if it is sought to obtain images with a resolution of 128.times.128 pixels and 32 images per heart cycle. In general, the reference point of the synchronization corresponds to the start of the cardiac cycle, i.e. the instant when the left ventricle is filled.
Furthermore, even if it were desired to accumulate strokes on a large number of cardiac cycles, for example more than 60 cycles (which corresponds to one minute), as is the usual practice, this could not lead to satisfactory results since, for the heart, the rhythm is not constant but depends on environmental conditions such as effort or exertion. Furthermore, the markers used and injected into the patient's body to create the scintigraphy image may be metabolized by the human body. Their radioactivity diminishes and, at the end of a certain period of time, the number of strokes that can be counted per period becomes insufficient.
Finally, another phenomenon comes into play: this is the choice of the marker injected into the patient's body. The marker generally chosen for injection in cardiac applications is thallium whose radioactive half-life is, unfortunately, 73 hours, whereas 99 m technetium, which is used for other applications but is less useful for the heart because it cannot be used alone, has a shorter radioactive half-life of the order of 6 hours. Thallium is preferred because it has the advantage of fixing well in the walls of the heart and, therefore, by the presence of this marker in the walls, of properly revealing the position of these walls. Unfortunately its greater half-life makes it necessary, in order to avoid traumatizing the patient with excessively large radioactive doses (proportional to the radioactive half-life of the marker) to inject smaller quantities of radioactive material. This again has the result of reducing the number of countable strokes.
The result of all these constraints is the obtaining of images with few strokes per pixel, hence images that are highly noise-ridden.
Examinations of another type have the same type of problem. These examinations are tomographies. In these tomographies, the individual being examined is supposed to be still, and the detector of the gamma camera is made to rotate about him so as to acquire a certain number of images or views, generally 64 of them. Since the acquisition of an image takes about 30 seconds, it means leaving the patient on the examination couch for about half an hour. It is hard to obtain a situation where the patient remains absolutely still during this period. The most irksome phenomenon in this type of examination is the metabolization of the marker and the fact that it is carried into the kidneys, namely into a pair of organs that are generally not monitored. The useful marking decreases accordingly. Thus, the number of strokes counted by images is ultimately small, and the images of the views are also noise-ridden.
To resolve the problems of noise in the images, various types of processing have been devised and perfected, notably in radiology. These processing operations are generally aimed at carrying out a spatial filtering of the image. A filtering such as this has the effect of modifying the image signal at a pixel so as to average it with the image signal of the neighboring pixels. This type of filtering, which may be tolerable when the resolution is very great (1024.times.1024 pixels) is hardly acceptable when the resolution is low as is generally the case in scintigraphy. In any case, it is done to the detriment of the precision of the image and to the detriment of the final resolution obtained.
There is another known type of processing. In this type of processing, it is assumed, for each pixel, that the image signal at this pixel evolves periodically as the general phenomen that is studied. This periodic evolution may be subjected to breakdown into Fourier series as a function of the harmonics of the variation of the phenomenon studied. In practice, a Fourier transform is carried out to recognize the amplitude and phase of each of the harmonics of the phenomenon. It has been shown that, for a batch of 16 images corresponding to 16 states of the heart, no statistically appreciable difference, measured with a khi.sup.2 test, is obtained between the 16 noise-ridden images obtained directly and 16 images that can be obtained again from the breakdown harmonics. This breakdown is of the following type: EQU A (t)=A.sub.0 =A.sub.1 cos (2.pi.f.sub.1 t+Phi.sub.1)+A.sub.2 cos (4.pi.f.sub.1 t+Phi.sub.2)+A.sub.3 cos (6.pi.f.sub.1 t+phi.sub.3)FORMULA I
In this formula, A is the luminance of a pixel, f.sub.1 is the frequency of the heartbeat and t is the time. To obtain the sixteen images, it is enough to give t a value ranging from 0 to 16 times the value of one-sixteenth of the period equal to 1/f.sup.1. It appears, however, that this type of filtering, which eliminates the harmonics beyond the third harmonic, is not a good filtering. It does eliminate the noise and the image does becomes more agreeable to look at but, in practice, it proves to be false, and it no longer reveals the phenomenon being studied owing to the elimination of its high frequencies.
An object of the invention is to overcome these drawbacks by a filtering processing operation that is applied no longer to the images obtained directly by the medical acquisition protocol or another protocol but to the analytic transformations of these images. In other words, to simplify matters, the sixteen initial images are taken. Analytic transforms are produced therefrom to obtain transformed images each having a real part and an imaginary part. The filtering of the noise is done on these transformed images. Preferably, the filtering is of the type referred to here above. However, it could be of a different type. Once this filtering is done, a reverse analytic transform is performed to return to images of a same type as the initial images. And a notable improvement is observed in the elimination of the noise.
The analytic transform in question is a spatial analytic transform which is preferably a Fourier transform, but it could also be a Z transform or any other mode of transformation. There is then a very sharp improvement, that is visible to the naked eye, of the signal-to-noise ratio of the images presented without incorporation of the noise in the image. Ultimately, the fact of using a spatial analytic transform of the original images (i.e. essentially in another dimension, that of time, rather than the dimension for which the spatial analytic transform is done) of each of the real and imaginary components makes it possible to search for a coherence that is not solely spatial or solely temporal as in the examples seen here above but a space-time combination of these images. The result then is far better.
The filtering proper can be improved not by placing a sharp limit on the analysis, into harmonics, of the real and imaginary parts beyond a given harmonic but, on the contrary, by damping the amplitudes of the harmonics greater than a harmonic of a given order, for example A3 (apodization).