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bioRxiv · 10.64898/2026.07.23.740284

Discrete Inverse Rendering: Biological Data Analysis with Integer Programming

Kirkegaard, J. B.·Zdyb, F. O.
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Abstract

Biological image and video analysis is full of discrete decisions: whether an object is present, which multi-hypothesis detections are real, whether two detections are tracking the same object, or whether a cell divides or not. Standard pipelines resolve these locally and in sequence, e.g through non-max suppression, per-frame segmentation, distance-based linking, or dedicated lineage rules. Image evidence and temporal evidence are thus rarely weighed against each other in a single objective. We recast these discrete steps as discrete inverse rendering : candidate renderings are generated, and then a integer programming solver selects the subset that best reconstructs the observed video subject to problem-specific constraints. We demonstrate that the same solver and the same reconstruction principle can handle three otherwise separate motifs: suppression of overlapping detections in dense C. elegans tracking, extraction of a single connected curve in sperm tracking, and event-structured tracking in single cell tracking.

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Kirkegaard, J. B., Zdyb, F. O.. 2026-07-27. Discrete Inverse Rendering: Biological Data Analysis with Integer Programming. https://doi.org/10.64898/2026.07.23.740284

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