The recognition of microcalcifications and masses from digital mammographic images are important to aid the detection of breast cancer. In this paper, we applied morphological techniques to extract the embedded structures from the images for subsequent analysis. A mammographic phantom was created with embedded structures such as micronodules, nodules and fibrils. For the preprocessing techniques, intensity transformation of gray scale was applied to the image. The structures of the image were enhanced and segmented using dilation for a morphological operation with morphological closing. Next, low pass Gaussian filter was applied to the image to smooth and reduce noises. It was found that our method improved the detection of microcalcifications and masses with high Peak Signal To Noise Ratio (PSNR).
The mass attenuation coefficients of solid water phantoms, Perspex® phantoms and Rhizophora spp. particleboards were determined by using Compton scattering technique measured using Ludlum configuration. The gamma energy of 137Cs sealed source were measured at 30°, 45°, 60° and 75° angles providing scattered gamma energies between 337.72 and 564.09 keV. The mass attenuation coefficients of solid water and fabricated Rhizophora spp. particleboards were the nearest to XCOM values of water with average percentage of discrepancies of 6.8% and 5.9%, respectively. The results indicated similar attenuation properties of solid water and fabricated Rhizophora spp. particleboards and the suitability of the Ludlum configuration to determine the mass attenuation coefficient of materials using Compton scatter technique.