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arXiv Machine Learning By John M. Statheros, Hairong Wang, Richard Klein

CLARiTy: A Vision Transformer for Multi-Label Classification and Weakly-Supervised Localization of Chest X-ray Pathologies

Read the original on arXiv Machine Learning →

CLARiTy is a vision transformer model that jointly performs multi‑label classification and weakly‑supervised localization of chest X‑ray pathologies. It uses class‑specific tokens to produce attention maps and a SegmentCAM module to refine foreground segmentation with anatomical priors. Trained on NIH ChestXray14 image‑level labels and distilled from a ConvNeXtV2 teacher, CLARiTy achieves competitive classification and strong localization, especially for small pathologies, outperforming prior methods by up to 50.7% relative Macro IoU accuracy.

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