Enhance registration precision of transmission breast images utilizing improved Levenberg-Marquardt optimization algorithm with normalized cross-correlation

Transmission imaging may become a possible advance for breast cancer screening with non-invasive, cost-effective, and radiation-free approaches for early detection. Frame accumulation can successfully eliminate the issue of low SNR, low grayscale and poor quality in transmission image. However, frame accumulation accuracy can be diminished because of inherent human body instability during image acquisition and the light absorption characteristics of breast tissue, resulting in distorted and misplaced image sequences. Therefore, improved Levenberg-Marquardt optimization algorithm with normalized cross-correlation is used as an innovative approach to rectify image sequences before frame accumulation processing. Two separate sets of data, showing breast images with and without markers, were collected using a halogen bulb and a mobile phone camera to validate the suggested method. The approach includes coarse registration utilizing normalized cross-correlation for initial value estimation, followed by fine registration using Levenberg-Marquardt algorithm. The results demonstrate a notable improvement in both accuracy of registration and frame accumulation quality. Specifically, the registration speed showed a remarkable increase, being 8.7 times faster, especially prominent in images that included markers. These images displayed normalized cross-correlation values reaching up to 0.99. The research emphasizes the future potential of the suggested method in overcoming the image quality challenges associated with breast transmission imaging, providing a significant milestone toward more accurate and efficient early breast cancer screening methods. Moreover, transmission imaging systems for the breast have been developed to verify the safety and effectiveness of the implemented technology.