Detection of metastatic liver tumor in multi-phase CT images by using a spherical gray-level differentiation searching filter

To detect the metastatic liver tumor on CT scans, two liver edge maps on unenhanced and portal venous phase images are firstly extracted and registered using phase-only correlation (POC) method, by which rotation and shift parameters are detected on two log-polar transformed power spectrum images. Then the liver gray map is obtained on non-contrast phase images by calculating the gray value within the region of edge map. The initial tumors are derived from the subtraction of edge and gray maps as well as referring to the score from the spherical gray-level differentiation searching (SGDS) filter. Finally the FPs are eliminated by shape and texture features. 12 normal cases and 25 cases with 44 metastatic liver tumors are used to test the performance of our algorithm, 86.7% of TPs are successfully extracted by our CAD system with 2.5 FPs per case. The result demonstrates that the POC is a robust method for the liver registration, and our proposed SGDS filter is effective to detect spherical shape tumor on CT images. It is expected that our CAD system could useful for quantitative assessment of metastatic liver tumor in clinical practice.