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arXiv Computer Vision By Christian Grashei, Fabian G\"ulhan, Maximilian Legnar, Fabian St\"ogbauer, Cleo-Aron Weis, Carolin Mogler, Peter Sch\"uffler

An end-to-end-trained vision-language model for native-language prostate pathology report generation

Read the original on arXiv Computer Vision →

An end-to-end-trained vision-language model generates prostate biopsy reports in native languages, demonstrated in German. The system uses a tokenizer and model trained from scratch and an automated pipeline that splits composite reports into image-text pairs, producing 17,344 pairs from 2,402 cases without manual annotation. Evaluated on clinical attributes, it achieves 96.2% F1 for malignancy detection and 65.2% for Gleason grading, comparable to an FDA-cleared classifier and validated on external cohorts.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

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