Andreas Rick

Development of contrast digital mammography.

Development of breast tumors is often accompanied by angiogenesis--the formation of new blood vessels. It is possible to image the effects of this process by tracking the uptake and washout of contrast agents in the vicinity of a lesion. In this article, a method for carrying out contrast subtraction mammography on a full-field digital mammography unit is described. Spectral measurements and modeling were performed to optimize the choice of x-ray target, kilovoltage and x-ray beam filtration for contrast digital mammography (CDM) on an available digital mammography system. Phantom studies were carried out to determine the sensitivity of CDM to iodine. Detection of iodine area densities of 0.3 mg/cm2 is possible for a circular object with a radius of 1.3 mm, which allows detection of uptake levels in the breast typically seen with cancer and some benign breast conditions. It was found that with a molybdenum anode x-ray tube, copper filtration could be used to effectively shape the x-ray spectrum to maximize the proportion of x rays with energies above the k edge of iodine. Simple logarithmic subtraction was found to be adequate in suppressing background signals dependent on the x-ray beam intensity and background thickness of the breast. The total x-ray dose from the procedure ranges between 1 and 3 mGy, similar to that from a conventional single view film mammogram. A clinical pilot study is currently being carried out to evaluate this technique.

Quantitative Modelling of Microcalcification Detection in Digital Mammography

This article presents a simulation framework for the image acquisition on digital mammography systems. The framework is used to analyse the performance of a previously developed method for the detection of microcalcifications by a series of top-hat operators. The framework allows to determine the theoretical number of false positives and true positives for a given set of acquisition parameters and size of microcalcifications.

Fuzzy Techniques in Mammographic Image Processing

In this chapter we discuss fuzzy techniques for the detection and analysis of potential breast cancer lesions on mammograms. We show how fuzzy measurements can be performed on the images and how this information can be used in the different stages of the processing.