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Visual NLP Blog

Visual NLP 3.3 enables DICOM de-identification at scale with DicomToImageV3 and DicomDrawRegions for secure medical imaging workflows.

Blog

Digital pathology is generating data faster than most healthcare organizations can safely share it. A single whole-slide image (WSI) can weigh in at several gigabytes, and every one of them...

DICOM de-identification is workflow-specific because PHI can appear in metadata tags, free-text metadata fields, burned-in image pixels, and encapsulated PDF content. A production pipeline may need to inspect tags, apply...

In the first two posts of this series, we benchmarked OCR on two increasingly demanding tasks: Grounded (BBox) OCR, reading text AND returning its coordinates Image → Markdown OCR, plain-text...

Most OCR tools tell you what a document says. That’s fine for search indexing and RAG. But when your workflow needs to act on a specific piece of text (redact...

In our first benchmark, we showed that JSL Vision OCR is the #1 grounded OCR model overall, beating every closed-source frontier system on the FUNSD dataset. This post answers a...
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