The field of ultrasound reconstruction and non-contact monitoring is witnessing significant advancements, driven by innovative applications of neural radiance fields, mmWave radar technologies, and machine learning algorithms. Researchers are exploring new approaches to improve the accuracy and efficiency of ultrasound imaging, such as acoustic-impedance-aware neural radiance fields and dual-supervised networks. Meanwhile, mmWave radar-based systems are being developed for non-contact vital sign monitoring, enabling simultaneous measurement of multiple patients' heart rates and breath rates. Noteworthy papers in this area include AIA-UltraNeRF, which achieves reconstruction and localization with inference speeds 9.9 times faster than vanilla NeRF. MapRF is another notable work, proposing a weakly supervised framework for online HD map construction via NeRF-guided self-training, achieving performance comparable to fully supervised methods.