GitHub - Zero-stargazer/DeepLISA: DeepLISA is an AI-assisted, physics-constrained image-analysis workflow for fluorescence microchamber digital assays, enabling auditable positive-chamber counting, candidate-level QC, overlay generation, and batch reporting for dPAC-CRISPR bioanalysis.

Branches Tags

Name		Name	Last commit message	Last commit date
Latest commit History 1 Commit
README_CN.md		README_CN.md
README_EN.md		README_EN.md
advanced_filtering.py		advanced_filtering.py
agent_batch_context.py		agent_batch_context.py
agent_core.py		agent_core.py
agent_quality.py		agent_quality.py
agent_tools.py		agent_tools.py
concentration_calculator.py		concentration_calculator.py
config.py		config.py
design_prior.py		design_prior.py
export_candidate_table.py		export_candidate_table.py
grid_detection.py		grid_detection.py
image_utils.py		image_utils.py
main.py		main.py
processing_pipeline.py		processing_pipeline.py
psf_verification.py		psf_verification.py
quality_control.py		quality_control.py
region_inference.py		region_inference.py
requirements.txt		requirements.txt
sample_analysis.py		sample_analysis.py
spatial_qc.py		spatial_qc.py

About

DeepLISA is an AI-assisted, physics-constrained image-analysis workflow for fluorescence microchamber digital assays, enabling auditable positive-chamber counting, candidate-level QC, overlay generation, and batch reporting for dPAC-CRISPR bioanalysis.