HamVision: Hamiltonian Dynamics as Inductive Bias for Medical Image Analysis
We present HamVision, a framework for medical image analysis that uses the damped harmonic oscillator, a fundamental building block of signal processing, as a structured inductive bias for both segmentation and classification tasks. The oscillator's phase-space decomposition yields three functionally distinct representations: position~$q$ (feature content), momentum~$p$ (spatial gradients that encode boundary and texture information), and energy $H = \tfrac{1}{2}|z|^2$ (a parameter-free saliency map). These representations emerge from the dynamics, not from supervision, and can be exploited by different task-specific heads without any modification to the oscillator itself. For segmentatio...
| Authors | Mohamed A Mabrok |
|---|---|
| Primary category | cs.CV |
| Published | 22 March 2026 |
| Last updated at source | 22 March 2026 |
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