Intracranial Hemorrhage (ICH)

Aidoc’s ICH solution is a triage and notification software indicated for use in the analysis of non-enhanced head CT images; flags and communicates suspected positive findings of pathologies in head CT images, namely Intracranial Hemorrhage (ICH).
Information source: Vendor
Last updated: Aug. 30, 2022

General Information

Product name Intracranial Hemorrhage (ICH)
Company Aidoc
Subspeciality Neuro
Modality CT
Disease targeted Intracranial Hemorrhage
Key-features Triage tool, workflow improvement
Suggested use Triage/prioritization of medical images.

Technical Specifications

Data characteristics
Population All non-contrast head CT
Input Non-contrast head CT
Input format DICOM
Output flagging and communication of positive suspected findings
Output format Annotated images: DICOM SC or overlay Prioritization notification: own application, HL7, API, bespoke integration
Integration Integration in standard reading environment (PACS), Integration RIS (Radiological Information System),
Deployment Hybrid solution
Trigger for analysis Automatically, right after the image acquisition
Processing time 1 - 10 minutes


Certified, Class I , MDD
FDA 510(k) cleared , Class II
Intended Use Statements
Intended use (according to CE) Radiological computer aided triage and notification software indicated for use in the analysis of head CT images. The device is intended to assist hospital networks and appropriately trained medical specialists in workflow triage by flagging and communication of suspected positive findings of Intracranial Hemorrhage (ICH).


Market presence
On market since 11-2017
Distribution channels Philips, Eureka Clinical AI, Nuance PIN, Fujifilm, Change Healthcare, GE Edison
Countries present (clinical, non-research use) 14
Paying clinical customers (institutes) Over 500
Research/test users (institutes) 20-30
Pricing model Subscription
Based on Total imaging volume


Peer reviewed papers on performance

  • Decreased Hospital Length of Stay for ICH and PE after Adoption of an Artificial Intelligence-Augmented Radiological Worklist Triage System (read)

  • Utilization of Artificial Intelligence–based Intracranial Hemorrhage Detection on Emergent Noncontrast CT Images in Clinical Workflow (read)

  • Diagnostic Accuracy and Failure Mode Analysis of a Deep Learning Algorithm for the Detection of Intracranial Hemorrhage (read)

  • Active Reprioritization of the Reading Worklist Using Artificial Intelligence Has a Beneficial Effect on the Turnaround Time for Interpretation of Head CT with Intracranial Hemorrhage (read)

  • Analysis of head CT scans flagged by deep learning software for acute intracranial hemorrhage (read)

Non-peer reviewed papers on performance

  • The utility of deep learning: evaluation of a convolutional neural network for detection of intracranial bleeds on non-contrast head computed tomography studies (read)

  • Preliminary Results of Aidoc's Deep Learning Algorithm Detection Accuracy for Pathological Intracranial Hyperdense Lesions (read)

  • Utility of Artificial Intelligence Tool as a Prospective Radiology Peer Reviewer -Detection of Unreported Intracranial Hemorrhage (read)

Other relevant papers

  • A prospective randomized clinical trial for measuring radiology study reporting time on Artificial Intelligence-based detection of intracranial hemorrhage in emergent care head CT (read)