Ultrasound is used for breast cancer detection as a technique complementary to mammography, the standard screening method. Current practice is based on reflectivity images obtained with conventional instruments by an operator who positions the ultrasonic transducer by hand over the patient’s body. It is a non-ionizing radiation, pain-free and not expensive technique that provides a higher contrast than mammography to discriminate among fluid-filled cysts and solid masses, especially for dense breast tissue. However, results are quite dependent on the operator’s skills, images are difficult to reproduce, and state-of-the-art instruments have a limited resolution and contrast to show micro-calcifications and to discriminate between lesions and the surrounding tissue. In spite of their advantages, these factors have precluded the use of ultrasound for screening.
This work approaches the ultrasound-based early detection of breast cancer with a different concept. A ring array with many elements to cover 360◦ around a hanging breast allows obtaining repeatable and operator-independent coronal slice images. Such an arrangement is well suited for multi-modal imaging that includes reflectivity, compounded, tomography, and phase coherence images for increased specificity in breast cancer detection. Preliminary work carried out with a mechanical emulation of the ring array and a standard breast phantom shows a high resolution and contrast, with an artifact-free capability provided by phase coherence processing.
Automated motion reduction in dynamic infrared imaging is on demand in clinical applications, since movement disarranges time−temperature series of each pixel, thus originating thermal artifacts that might bias the clinical decision. All previously proposed registration methods are feature based algorithms requiring manual intervention. The aim of this work is to optimize the registration strategy specifically for Breast Dynamic Infrared Imaging and to make it user−independent. We implemented and evaluated 3 different 3D time−series registration methods: 1. Linear affine, 2. Non−linear Bspline, 3. Demons applied to 12 datasets of healthy breast thermal images. The results are evaluated through normalized mutual information with average values of 0.70 ±0.03, 0.74 ±0.03 and 0.81 ±0.09 (out of 1) for Affine, Bspline and Demons registration, respectively, as well as breast boundary overlap and Jacobian determinant of the deformation field. The statistical analysis of the results showed that symmetric diffeomorphic Demons’ registration method outperforms also with the best breast alignment and non−negative Jacobian values which guarantee image similarity and anatomical consistency of the transformation, due to homologous forces enforcing the pixel geometric disparities to be shortened on all the frames. We propose Demons’ registration as an effective technique for time−series dynamic infrared registration, to stabilize the local temperature oscillation.