A Kalman filtering framework for virtual sensor–enhanced photoacoustic imaging (opens in new tab)

Photoacoustic imaging (PAI) combines the high contrast of optical absorption with the spatial resolution of ultrasound detection; however, its performance is often constrained by incomplete angular sampling and measurement noise. In this work, we introduce a model-based Kalman filtering framework for estimating virtual sensor measurements at intermediate angular positions of a circular detection array.Instead of adding new detector elements, the method generates statistically consistent virtu...