Segmented Head Anatomical Reference Model

Segmented Head Anatomical Reference Models (SHARMs) are digital representations of the human head, segmented into various anatomical tissues like bone, muscle, and brain structures. Current research focuses on creating accurate and comprehensive SHARMs using techniques like convolutional neural networks and photogrammetry, often incorporating deep learning for denoising and improving the quality of input scans. These models are crucial for diverse applications, including medical imaging analysis, surgical planning, virtual reality, and the development of more realistic simulations for fields like electromagnetic dosimetry and audio rendering. The availability of large, high-quality SHARMs datasets is driving advancements in these areas.