An X-ray CT (Computed Tomography) apparatus calculates an X-ray absorption coefficient at each point from the measured projection data that is obtained by imaging a subject from multi-directions, and obtains as a tomographic image of a subject, an X-ray absorption coefficient distribution image (hereinafter, referred to as “CT image”) made up of plural pixels. The CT image acquired through this apparatus allows a patient's disease condition to be diagnosed accurately and immediately in medical practice, and it is clinically effective. However, a constant amount of radiation exposure is unavoidable in order to acquire an image of high quality necessary for diagnosis by a doctor. On the other hand, if the radiation dose is lowered in order to implement low dose scanning, a noise ratio increases to the signals being detected, and a large amount of linear streak artifact and/or graininess noise may occur, causing erroneous diagnosis. Therefore, it is desired to reduce such streak artifact and noise in the low dose scanning, and to achieve compatibility between high-quality diagnosis and low dose scanning.
In view of the situation above, the Patent Document 1 describes that there is employed an iterative approximate reconstruction method to iteratively correct a CT image so as to satisfy the condition that the calculated projection data is equal to the measured projection data, and reduce the noise. In the iterative approximate reconstruction method, firstly, a reconstructing process is performed on the region for reconstruction (hereinafter, referred to as “FOV”) including the subject, and an image (FOV image) is obtained. Next, projection data is calculated from the reconstructed image (FOV image) (hereinafter, referred to as “forward projection calculation”), and iterates the operation for correcting the CT image, in comparison to the aforementioned measured projection data. This may enhance the precision of the CT image within the FOV. The iterative approximate reconstruction method requires the condition that the FOV incorporates the subject therein, and therefore, if the correction of the subject is unrelated to the diagnosis, it may cause increase of the calculation amount.
As a publicly known analytical reconstruction method, an extensive reconstruction method is suggested to perform reconstruction operation on a local region, so as to reduce the calculation amount. In view of this, it is conceivable to apply the extensive reconstruction technique to the iterative approximate reconstruction method, and reduce the calculation amount. However, in the iterative approximate reconstruction method, it is difficult to perform the reconstruction operation only on the local region out of the measured projection data, and therefore, it is necessary to extract from the measured projection data, projection data being included in the local region (hereinafter, referred to as “local measured projection data”).
The Non Patent Document 1 discloses a technique that applies the extensive reconstruction technique to the iterative approximate reconstruction method. This technique reconstructs a CT image on the FOV incorporating the subject with a table, a fixture, and the like (hereinafter, referred to as “large FOV image”). Next, an image of a background region other than the local region is extracted from the large FOV image, and thus extracted image of the background region is subjected to the forward projection calculation, thereby obtaining background projection data. Thus obtained background projection data is subtracted from the measured projection data, thereby extracting local measured projection data, and calculating the CT image of the local region (hereinafter, referred to as “small FOV image”). Accordingly, it is possible to apply the iterative approximate reconstruction method to the local measured projection data, and improve the precision of the small FOV image.
On the other hand, in the analytical reconstruction method, when data obtained at some projection angles fails to be measured on the periphery of the FOV, it is known that the precision of the CT image of the FOV is remarkably deteriorated (incomplete reconstruction). The Patent Document 2 advises to estimate the subject within the region where data is unmeasurable on the periphery of the FOV, thereby improving the precision of a CT value (X-ray absorption value) in the FOV image.