Democratizing Pathological Image Segmentation with Lay Annotators via Molecular-empowered Learning

doi:doi:10.57702/b7adnp8w

Democratizing Pathological Image Segmentation with Lay Annotators via Molecular-empowered Learning

Multi-class cell segmentation in high-resolution Giga-pixel whole slide images (WSI) is critical for various clinical applications. Training such an AI model typically requires labor-intensive pixel-wise manual annotation from experienced domain experts (e.g., pathologists). Moreover, such annotation is error-prone when differentiating fine-grained cell types (e.g., podocyte and mesangial cells) via the naked human eye.

BibTex:

@dataset{Ruining_Deng_and_Yanwei_Li_and_Peize_Li_and_Jiacheng_Wang_and_Lucas_W_Remedios_and_Saydolimkhon_Agzamkhodjaev_and_Zuhayr_Asad_and_Quan_Liu_and_Can_Cui_and_Yaohong_Wang_and_Yihan_Wang_and_Yucheng_Tang_and_Haichun_Yang_and_Yuankai_Huo_2024,
    abstract = {Multi-class cell segmentation in high-resolution Giga-pixel whole slide images (WSI) is critical for various clinical applications. Training such an AI model typically requires labor-intensive pixel-wise manual annotation from experienced domain experts (e.g., pathologists). Moreover, such annotation is error-prone when differentiating fine-grained cell types (e.g., podocyte and mesangial cells) via the naked human eye.},
    author = {Ruining Deng and Yanwei Li and Peize Li and Jiacheng Wang and Lucas W. Remedios and Saydolimkhon Agzamkhodjaev and Zuhayr Asad and Quan Liu and Can Cui and Yaohong Wang and Yihan Wang and Yucheng Tang and Haichun Yang and Yuankai Huo},
    doi = {10.57702/b7adnp8w},
    institution = {No Organization},
    keyword = {'cell segmentation', 'image annotation', 'lay annotators', 'molecular-empowered learning', 'pathology'},
    month = {dec},
    publisher = {TIB},
    title = {Democratizing Pathological Image Segmentation with Lay Annotators via Molecular-empowered Learning},
    url = {https://service.tib.eu/ldmservice/dataset/democratizing-pathological-image-segmentation-with-lay-annotators-via-molecular-empowered-learning},
    year = {2024}
}