MycorrhiSEE: a High-Resolution Image Dataset for Deep Learning Based Quantification of Arbuscular Mycorrhizal Fungi

Developing deep learning tools for automated quantification of arbuscular mycorrhizal fungi (AMF) necessitates large, high-quality datasets capturing the diversity of AMF-root interactions under varied environmental conditions. We present MycorrhiSEE, a 15-Terabyte (Tb), high-resolution image dataset comprising approximately 137,500 whole-slide images (WSIs) of root segments from 5,500 sorghum plants representing 337 genotypes, grown under diverse agronomic treatments. Images were acquired using the ZEISS AxioScan 7 high-throughput robotic microscope equipped with a 5-megapixel resolution color camera. This dataset provides unprecedented detail and diversity, offering a valuable resource for developing deep learning applications in AMF research.