Quibim review
A cloud imaging platform for clinical and research teams working with DICOM and biomarkers.
Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
Quibim provides cloud-based medical imaging software for hospitals, research institutions and biopharmaceutical teams. Its QP-Insights platform manages, harmonizes, stores and analyzes DICOM and multi-omics data, with AI-driven segmentation, radiomics extraction, treatment-response assessment and biomarker quantification. This makes it relevant to organizations analyzing clinical imaging and linking image findings with research or clinical data workflows, rather than teams looking for a general-purpose segmentation tool.
The standout capability is the combination of segmentation and imaging analysis. Quibim supports organ and lesion segmentation, automatic prostate-region segmentation, and tumor-lesion segmentation for PSMA PET and FDG PET. It can also detect, measure and track lesions with RECIST 1.1, extract radiomics features from regions of interest, and generate structured reports with imaging-biomarker quantification. A DICOM viewer includes annotation and manual segmentation tools. These features suit teams needing more than a mask-generation workflow, particularly where treatment response and quantitative imaging are central.
Platform fit is oriented around existing medical-data systems: QP-Link supports DICOM storage and transfer and PACS integration, while listed connections include DICOMweb, EHR, EDC/eCRF and fusion biopsy systems. The platform is cloud-deployed, and Quibim describes a SaaS model with prospects directed to contact or demo requests rather than self-service purchase. Its stated safeguards include anonymization, encryption and audit logging, with ISO 27001, GDPR, HIPAA and two-factor authentication listed. Healthcare organizations with cloud-ready imaging workflows and a need for integrated analysis should consider it; teams requiring local deployment or straightforward self-serve adoption should look elsewhere.
Quibim pros and cons
- Where it wins
- AI organ and lesion segmentation, including prostate and PET workflows
- DICOM and PACS tools connect imaging with clinical data systems
- Radiomics, biomarker quantification and structured reports
- Where it doesn't
- Sales-led access may slow teams seeking self-service adoption
- Cloud-only deployment may not suit teams requiring local hosting
- Focus on medical imaging is not suited to general-purpose image segmentation
Quibim fact sheet, pricing and score →
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