Large-vocabulary forensic pathological analyses via prototypical cross-modal contrastive learning

Chen Shen; Chunfeng Lian; Wanqing Zhang; Fan Wang; Jianhua Zhang; Shuanliang Fan; Xin Wei; Gongji Wang; Kehan Li; Hongshu Mu; Hao Wu; Xinggong Liang; Jianhua Ma; Zhenyuan Wang

doi:10.1038/s41467-025-62060-x

arXiv · 2407.14904

Large-vocabulary forensic pathological analyses via prototypical cross-modal contrastive learning

Chen Shen·Chunfeng Lian·Wanqing Zhang·Fan Wang·Jianhua Zhang·Shuanliang Fan·Xin Wei·Gongji Wang·Kehan Li·Hongshu Mu·Hao Wu·Xinggong Liang·Jianhua Ma·Zhenyuan Wang

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Abstract

Forensic pathology is critical in determining the cause and manner of death through post-mortem examinations, both macroscopic and microscopic. The field, however, grapples with issues such as outcome variability, laborious processes, and a scarcity of trained professionals. This paper presents SongCi, an innovative visual-language model (VLM) designed specifically for forensic pathology. SongCi utilizes advanced prototypical cross-modal self-supervised contrastive learning to enhance the accuracy, efficiency, and generalizability of forensic analyses. It was pre-trained and evaluated on a comprehensive multi-center dataset, which includes over 16 million high-resolution image patches, 2,228 vision-language pairs of post-mortem whole slide images (WSIs), and corresponding gross key findings, along with 471 distinct diagnostic outcomes. Our findings indicate that SongCi surpasses existing multi-modal AI models in many forensic pathology tasks, performs comparably to experienced forensic pathologists and significantly better than less experienced ones, and provides detailed multi-modal explainability, offering critical assistance in forensic investigations. To the best of our knowledge, SongCi is the first VLM specifically developed for forensic pathological analysis and the first large-vocabulary computational pathology (CPath) model that directly processes gigapixel WSIs in forensic science.

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Chen Shen, Chunfeng Lian, Wanqing Zhang, Fan Wang, Jianhua Zhang, Shuanliang Fan, Xin Wei, Gongji Wang, Kehan Li, Hongshu Mu, Hao Wu, Xinggong Liang, Jianhua Ma, Zhenyuan Wang. 2024-07-20. Large-vocabulary forensic pathological analyses via prototypical cross-modal contrastive learning. https://doi.org/10.1038/s41467-025-62060-x

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