Evaluating Neural Implicit Representations for High-Resolution Cryo-EM Reconstruction
Continuous Volume Field Recovery Beyond the Nyquist Limit
Cryogenic electron microscopy (Cryo-EM) is hindered by severe signal-to-noise attenuation and conformational heterogeneity in macromolecular complexes. We formulate Cryo-NeRF, a coordinate-based continuous neural field parameterized by Fourier feature embeddings and coordinate-aware volume rendering that jointly refines 3D voxel density and pose orientation angles. Evaluations on benchmark ribosome datasets (EMPIAR-10028) reveal resolution improvements from 2.9Å to 2.1Å without requiring discrete conformational binning. Neural implicit representations provide a differentiable, bias-free pathway for atomic-level macromolecular modeling directly from noisy micrograph projections.