MediPPD: Vision-Language Metrology Meets Dermal Interpretation in Purified Protein Derivative Skin Tests

Automated Purified Protein Derivative (PPD) skin-test assessment requires both millimeter-scale quantification of clinician-measured induration and localized interpretation of clinically relevant dermal findings. However, these objectives present two challenges: (1) Metric Fidelity Gap, where semantic representations may lose the geometric and scale information required for accurate physical measurement; (2) Spatial Grounding Failure, where correct semantic predictions may lack localized evidence supporting the identified dermal findings. To systematically examine these challenges, we establish a unified benchmark that links clinician-defined induration to calibrated physical measurement and dermal-sign predictions to localized evidence, enabling joint evaluation of metric fidelity and clinically meaningful grounding. To address the distinct representational requirements revealed by this benchmark, we propose MediPPD: Vision-Language Metrology Meets Dermal Interpretation in Purified Protein Derivative Skin Tests, which adopts selective separation with controlled interaction to preserve geometry-sensitive physical metrology while allowing calibrated geometry to support semantic reasoning, thereby enabling accurate measurement together with spatially grounded dermal interpretation. Extensive experiments demonstrate that MediPPD consistently improves physical measurement and grounded dermal interpretation over competitive visual and multimodal methods.