CBCT image processing method

A method for multi-dimensional image processing comprising:

• obtaining a multi-dimensional image having a plurality of data elements, each data element having a corresponding data value;
• forming a reduced noise image by a plurality of process iterations estimating the data value for each of one or more data elements of interest p of the obtained image, after obtaining an initial estimate for the data element of interest p, by:
• (i) for each data element k in a group of data elements in the image, calculating a weighting factor for the data element k as a function of the difference between the estimated data value for the data element p and the corresponding data value of the data element k;
• and
• (ii) updating the estimated data value for the data element p according to the combined calculated weighting factors and the data value of the data element k;
• and
• displaying, storing, or transmitting the reduced noise image,
• wherein the weighting factor is a first weighting factor and further comprising applying a second weighting factor to the data element of interest by:
• i) selecting a local region about the data element of interest and a corresponding region about another data element;
• ii) for each local data element in the local region about the data element of interest, calculating a similarity metric based on the difference value between the local data element and a corresponding data element within the corresponding region about the other data element;
• and
• iii) calculating the second weighing factor according to the sum of similarity metric values.

A method of noise filtering a multi-dimensional image that includes multiple data elements including the steps of:

• a) selecting a data element of interest;
• b) calculating a reduced noise value for the data element of interest using a combination of a first and second weighting factor;
• c) combining the first and second weighting factors to calculate the reduced noise value for the data element of interest;
• d) repeating steps b) and c) for other data elements in the multi-dimensional image to form the reduced noise multi-dimensional image;
• and
• e) storing, transmitting, or displaying the reduced noise multi-dimensional image on a display,
• wherein the second weighting factor for each other data element is calculated by:
• i) selecting a region about the data element of interest and a corresponding region about the other data element;
• ii) for each local data element in the region about the data element of interest, calculating a similarity metric based on the difference value between the local data element and its corresponding local data element in the region within the region about the other data element;
• and
• iii) calculating the second weighing factor as the sum of similarity metric values.