U-FISH: a fluorescent spot detector for imaging-based spatial-omics analysis and AI-assisted FISH diagnosis
Year: 2025
Type: article
Abstract: Imaging-based spatial-omics advances biomedical discoveries with subcellular resolution and high sensitivity, but accurately identifying signal spots from diverse images remains challenging. We develop U-FISH, a deep learning method that enhances images for consistent spot detection across various spatial-omics data. We establish a comprehensive FISH image dataset from seven spatial-omics methods. Benchmark analysis shows U-FISH has superior accuracy and generalizability compared to existing methods and can effectively decode 3D FISH data. U-FISH is the first spot detection software integrated with large language models, as demonstrated in AI-assisted diagnostics. Our study provides a valuable tool for spatial-omics analysis and diagnostics.
Source: Genome biology
Institutions: Huazhong Agricultural University, Stanford Medicine, State Key Laboratory of Agricultural Microbiology, Shenzhen University of Advanced Technology, Stanford University, Chinese Academy of Medical Sciences & Peking Union Medical College, Institute of Hematology & Blood Diseases Hospital, Institut Pasteur, Université Paris Cité, Hong Kong University of Science and Technology, Science for Life Laboratory, KTH Royal Institute of Technology, Chinese Academy of Sciences, Shenzhen Institutes of Advanced Technology
Language: English
Subfield: Biophysics
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $5,490
Awards: G2173389461, G8519090647
OpenAlex ID: W4413873956