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FluoCLIP: Stain-Aware Focus Quality Assessment in Fluorescence Microscopy

CVPR 2026 · Vision-language and multimodal › Multimodal LLMs · approach: Multimodal LLM benchmarks · 0 citations (OpenAlex)

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Proposes stain-aware focus quality assessment for fluorescence microscopy, a two-stage CLIP-based ordinal framework (FluoCLIP) and the FluoMix dataset, showing it beats CLIP-based and conventional FQA baselines.

Problem

Focus quality assessment in fluorescence microscopy, where stain-dependent optics break the shared global focus-rank ordering assumed by existing stain-agnostic FQA methods.

Approach

Learn grounded stain tokens by aligning them with CLIP visual features in a first stage (with frozen text encoder plus adapter), then condition interpolated ordinal rank prompts on the stain embedding in a second stage, so focus ranking is stain-specific.

Key results

• On FluoMix with ResNet50, FluoCLIP reaches 85.21% accuracy versus 83.12% for OrdinalCLIP and 54.59% for cross-entropy baseline.
• With ViT-B/16 on FluoMix, FluoCLIP reaches 90.75% accuracy versus 89.95% for OrdinalCLIP and 83.99% for BiomedCLIP.
• On BBBC006, FluoCLIP reaches 93.05% accuracy versus 90.67% for OrdinalCLIP; on FocusPath it is slightly lower than OrdinalCLIP (91.11% vs 94.98%).

Surprising findings

• On FocusPath (bright-field), adding stain-conditioned prompts slightly hurts accuracy relative to OrdinalCLIP.
• Learnable stain tokens without grounding reduce accuracy below the baseline (81.38% vs 83.12%).

Limitations

• Assumes predefined stain categories; automatic stain discovery not addressed.
• Relative annotation scheme (10 levels derived from z-stack position) rather than continuous focus scores.
• FluoCLIP underperforms OrdinalCLIP on FocusPath and at very low shot counts in few-shot experiments.

Experimental setup

Datasets: FluoMix BBBC006 FocusPath

Benchmarks: FluoMix BBBC006 FocusPath

Metrics: accuracy PLCC SRCC MAE

Baselines: FocusLiteNN CE OE CO2 QULCE CLIP OrdinalCLIP NumCLIP BiomedCLIP PubMedCLIP PMC-CLIP CoOp

Builds on: CLIP OrdinalCLIP CoOp NumCLIP BiomedCLIP

Closest papers by meaning

• scSplit: Bringing Severity Cognizance to Image Decomposition in Fluorescence Microscopy (NeurIPS 2025 · similarity 0.85)
• Micro-Bench: A Microscopy Benchmark for Vision-Language Understanding (NeurIPS 2024 · similarity 0.84)
• MorphoHELM: A Comprehensive Benchmark for Evaluating Representations for Microscopy-Based Morphology Assays (NeurIPS 2026 · similarity 0.83)
• ViTally Consistent: Scaling Biological Representation Learning for Cell Microscopy (ICML 2025 · similarity 0.83)
• SheafStain: Sheaf-Theoretic Schr\"odinger Bridge for Spatially and Biologically Coherent Virtual Staining (NeurIPS 2026 · similarity 0.83)
• CellCLIP - Learning Perturbation Effects in Cell Painting via Text-Guided Contrastive Learning (NeurIPS 2025 · similarity 0.82)