Pre-Procedural Planning Support
IR procedure planning models segment vessels, measure lesion dimensions, and organize prior imaging so the interventionalist reviews a prepared dataset before the case rather than reconstructing measurements manually.
Custom Software
AI Interventional Radiology Software Development
AI interventional radiology software applies machine learning to pre-procedural imaging, intra-procedural guidance data, and post-procedure outcomes tracking to support IR teams with planning, measurement, and documentation. It functions as decision support only: the interventionalist makes every procedural, device, and treatment decision.
Interventional radiology combines diagnostic imaging with real-time procedural work, which makes it one of the harder settings for software to fit into without adding friction. Taction Software builds AI interventional radiology tooling that supports planning and documentation around the procedure rather than interfering during it. Every build is designed for physician control, auditability, and integration with systems your IR suite already runs.
Tell Us Your Requirements
Our experts are ready to understand your business goals.
Trusted Partners
Trusted by Industry Leaders Worldwide
Recognition
Awards & Recognitions
What Is AI Interventional Radiology
AI interventional radiology refers to machine learning, computer vision, and workflow automation applied to image-guided minimally invasive procedures: embolization, angioplasty, ablation, biopsy, drainage, and vascular access. Models work across CT, MR, ultrasound, fluoroscopy, and cone-beam CT, supporting vessel segmentation, target measurement, device sizing reference, and structured procedural documentation. These systems are assistive by definition. They surface measurements and prior-study context, but the interventionalist confirms every input and makes all clinical decisions. This work sits inside our wider healthcare AI practice, where validation, bias monitoring, and regulatory classification are handled as engineering deliverables rather than late-stage paperwork.
Image-Guided Intervention Assistance
Image-guided intervention support includes registration between pre-procedural CT or MR and intra-procedural fluoroscopy, giving the operator overlay reference that is reviewed and adjusted at the console.
Vascular Segmentation and Mapping
Vessel segmentation produces arterial and venous maps from CTA or MRA volumes, generating vascular anatomy models the physician verifies before using them for access route consideration.
Radiation Dose Tracking
Fluoroscopy dose tracking captures air kerma, dose area product, and screening time per case, supporting departmental dose optimization review and regulatory reporting obligations.
Structured Procedure Documentation
Automated capture of device, contrast, and step data populates procedure reports, replacing manual transcription while keeping physician review of the finalized narrative mandatory.
Decision Support Boundaries
Every output is labeled clinical decision support. The software proposes measurements and reference information. It does not select devices, authorize interventions, or make diagnostic determinations under any configuration we build.
Core AI Interventional Radiology Services
Our AI interventional radiology services cover feasibility assessment, model development, integration with imaging and hospital systems, and long-term monitoring. IR is integration-heavy: a useful tool has to reach the planning workstation, the angiography suite, the RIS, and the registry submission pipeline. We scope those interfaces explicitly rather than treating them as implementation detail. Engagements typically begin with a review of imaging archives, dose management data, and existing reporting workflows, because data condition determines feasibility more than model choice. Deliverables are structured so clinical, IT, and compliance stakeholders can each review their portion independently before anything reaches a live procedural environment.
01
Custom Model Development
We train custom segmentation and measurement models on institutional imaging, documenting training data provenance, held-out evaluation, and subgroup performance before any clinical pilot begins.
02
Planning Workstation Integration
Integration delivers model output into the planning workstation the IR team already uses, so prepared measurements appear in existing review software instead of a separate application.
03
PACS and DICOM Interfaces
We implement DICOM query, retrieve, storage, and Structured Reporting against your archive. The PACS architecture reference covers the systems this layer touches.
04
Cath Lab and Angiography Data Capture
We build interfaces to angiography suite equipment and hemodynamic systems, capturing dose, device, and timing data automatically for documentation and quality review.
05
Registry and Reporting Automation
Automated extraction populates quality registry submissions and departmental dashboards from verified procedural data, reducing the manual abstraction burden on IR coordinators.
06
Model Monitoring and Revalidation
Post-launch we instrument drift detection, equipment-level performance tracking, and fairness monitoring across patient subgroups, with defined thresholds and rollback triggers.
Benefits of AI Interventional Radiology
The benefits of AI interventional radiology software concentrate in preparation time, documentation completeness, and data availability for quality review. IR teams spend meaningful effort on pre-case measurement, post-case dictation, and registry abstraction, all of which are structured tasks that software handles consistently. Better structured data also improves dose review and outcomes tracking, which currently depend on manual abstraction in many departments. We do not publish throughput or efficacy figures, because those depend on your case mix, staffing, and current baseline. What we provide is instrumentation, so your team measures impact against your own operational data rather than a vendor claim.
Faster Case Preparation
Pre-populated segmentation and measurement reduce manual planning steps, easing IR suite workflow pressure in departments running high case volumes with limited physician preparation time.
More Complete Documentation
Automated capture of device, contrast, and dose data produces more complete procedure reports, reducing gaps that later complicate billing, quality review, and registry submission.
Improved Dose Oversight
Systematic radiation dose tracking per operator, procedure type, and equipment supports departmental review and identifies cases warranting protocol attention, with physicians interpreting all findings.
Measurement Consistency
Automated quantification reduces inter-operator variability in lesion and vessel measurement, producing values that compare more reliably across cases and over time.
Reduced Abstraction Burden
Registry submission drawn from structured capture rather than manual chart review lowers quality reporting effort for coordinators managing multiple national registries.
Better Multidisciplinary Coordination
Structured procedural data flows into tumor board and vascular conference discussions more cleanly, complementing the workflows described on our oncology AI page.
Our AI Interventional Radiology Process
We deliver AI interventional radiology projects in gated phases so clinical stakeholders approve direction before engineering cost accumulates. Discovery establishes intended use, available data, and regulatory classification, because software making procedural claims carries different obligations than internal measurement tooling. Development is iterative with interventionalist review inside each cycle. Deployment is staged: shadow mode first, then limited availability, then broader rollout. This sequencing matters in IR because equipment configuration, contrast protocols, and operator technique vary between suites, and model behavior against real institutional data is the only reliable signal of readiness.
Discovery and Regulatory Assessment
Discovery defines intended use, evaluates archive condition, and assesses whether SaMD classification applies, then produces a fixed-scope estimate with a documented regulatory pathway.
Data Preparation and Annotation
We build de-identified training sets and annotation protocols, measuring inter-annotator agreement, since ground truth quality constrains model performance more than architecture selection.
Model Development and Validation
Development runs from cross-validation through external validation, reporting results by scanner, contrast protocol, and patient subgroup so limitations are documented rather than averaged away.
Workflow and Systems Integration
Integration connects archive routing, worklists, and reporting. Our radiology information system development work covers the RIS integration patterns applied here.
Shadow Mode Evaluation
The system runs in shadow deployment first, logging output alongside physician work so your team compares agreement and identifies failure modes without any patient impact.
Staged Rollout and Support
Rollout expands by operator and procedure type, with performance dashboards, agreed rollback triggers, and continuing post-deployment surveillance for the life of the deployment.
Technology and Compliance
IR software touches PHI, imaging archives, dose records, and in some configurations procedural planning data, so compliance is designed in from the first sprint rather than retrofitted. Taction holds ISO 27001 certification and follows HIPAA-aligned engineering practice. Where intended use implies procedural or diagnostic claims, the software may meet the definition of Software as a Medical Device, which changes validation, documentation, and change control obligations substantially. We assess classification during discovery. Technically we build on standards-based imaging interfaces, containerized inference, and audit logging detailed enough to reconstruct any individual result after the fact.
HIPAA-Aligned Engineering
Builds implement encryption in transit and at rest, role-based access control, and complete audit logging. Our HIPAA compliance software development practice defines these baseline controls.
SaMD and FDA Considerations
Where intended use implies procedural claims, SaMD classification applies. Our FDA SaMD compliance services cover design history, validation records, and change control.
Imaging Standards and Interoperability
We implement DICOM services, DICOM Structured Reporting, and FHIR resources so verified results move between imaging and clinical systems without manual re-entry.
Model Validation and Bias Monitoring
Validation reports performance by equipment model, protocol, and patient subgroup, with continuing bias monitoring, because equipment and population shifts change model behavior over time.
Generative Output Controls
Where models draft report narrative, we treat hallucination risk as a design constraint: text stays grounded in captured procedural data, and physician review of every generated passage is required.
Infrastructure and Deployment Security
Deployments run on-premise, in your cloud tenancy, or hybrid, with network segmentation, signed container images, and documented penetration testing before production release.
Why Choose Taction Software
Taction Software was founded in 2013 and has spent over 12 years building healthcare software, delivering more than 200 healthcare projects. We work from four US offices in Chicago, Cheyenne, Austin, and Sacramento, and hold ISO 27001 certification. Our credibility in imaging and procedural software comes from delivery: we have built EHR and EMR platforms, FDA-registered mobile applications, and behavioral health systems, which means the regulatory and integration constraints that stall IR projects are familiar territory. Our leadership brings more than 20 years of personal experience in the field, and that judgment shapes how we scope regulated work.
01
Established Healthcare Focus
Founded in 2013, we have concentrated on healthcare rather than treating it as one vertical among many, producing practical depth in clinical workflow and imaging system constraints.
02
Regulated Product Experience
We delivered the FDA-registered applications Revive Ease and PainKare, so design controls, validation documentation, and change management are established practice rather than new territory.
03
EHR and Clinical Systems Depth
Our Voyant Health EHR and EMR work means EHR integration is handled by engineers who have built systems on both sides of the interface rather than only consuming an API.
04
Sensitive Data Handling
Delivering CHIPSS for behavioral health required strict data segmentation and consent handling, experience that transfers directly to imaging and procedural records.
05
US-Based Delivery Teams
Four US offices support overlapping working hours, on-site discovery sessions, and direct engineer access, which shortens stakeholder review cycles on regulated builds.
06
Certified Security Posture
ISO 27001 certification and HIPAA-aligned engineering mean security controls are documented and auditable, supporting your vendor risk assessment without a lengthy remediation phase.
Pricing
AI interventional radiology pricing depends on scope, data condition, integration surface, and regulatory pathway. Integrating an existing cleared algorithm into a planning workflow costs considerably less than training a custom model requiring external validation and an FDA submission. We price after discovery rather than before, because IR data condition and equipment heterogeneity vary widely between institutions and drive a large share of total effort. Discovery produces an itemized, fixed-scope estimate with phase-level breakdown so you can approve or defer components. Third-party algorithm licensing, cloud infrastructure, and equipment vendor interface fees are separate from engineering cost and itemized clearly.
MVP or Single Module
An MVP covering one procedure type, one analysis task, and basic archive integration typically runs $40,000 to $80,000, suitable for validating clinical value before wider commitment.
Full Platform Build
A full platform with multiple analysis pipelines, planning integration, documentation automation, and monitoring typically falls between $80,000 and $200,000 depending on validation depth.
Enterprise Deployment
Enterprise engagements covering multi-site rollout, custom model training, external validation, and regulatory documentation start at $200,000 and scale with site count and submission scope.
Discovery Phase Scoping
Discovery is a paid, time-boxed phase producing an itemized estimate, architecture plan, and regulatory assessment. It is deliberately separable so you can evaluate our work before committing further.
Cost Drivers to Expect
Annotation volume, external validation requirements, equipment heterogeneity, and SaMD documentation are the largest variables. Each is identified during discovery so budget planning reflects real effort.
Ongoing Support Costs
Post-launch model monitoring, retraining cycles, and support are quoted separately as a retainer sized to your deployment footprint and revalidation cadence.
Get Started
If you are evaluating AI interventional radiology tooling for planning, documentation, or dose oversight in your IR suite, the fastest next step is a discovery call with our clinical engineering team. We will review your imaging archives, equipment configuration, and intended use, then return an itemized, fixed-scope estimate alongside a clear regulatory assessment. Contact us to schedule that conversation.
FAQs
Frequently Asked Questions
Teams evaluating AI interventional radiology software tend to raise three concerns: whether software influences procedural decisions, what regulatory obligations the intended use creates, and what reaching a validated production deployment costs. The answers below reflect how we scope and deliver these projects in practice. If your situation involves a novel technique, a mixed-vendor angiography environment, or an intended use likely to require FDA submission, the specifics matter more than any general answer, and a discovery conversation will be more useful than a page.
No. Every tool we build operates as clinical decision support. The system proposes measurements, segmentations, and reference information, and the interventionalist confirms, edits, or rejects each output. Physician confirmation is a required and logged workflow step. We do not build autonomous device selection, treatment authorization, or diagnostic determination, and we make no efficacy claims about model output.
It depends on intended use. Software making procedural or diagnostic claims may meet the definition of Software as a Medical Device and require a regulatory pathway, while internal measurement and documentation tooling often does not. We assess classification during discovery and build the design controls and validation documentation the applicable pathway requires.
An MVP or single module runs $40,000 to $80,000. A full platform typically falls between $80,000 and $200,000. Enterprise deployments with multi-site rollout and regulatory documentation start at $200,000. Discovery produces an itemized, fixed-scope estimate, and third-party licensing and infrastructure are quoted separately from engineering.
In most cases yes, through standards-based interfaces and vendor-supported data export. Capability varies by manufacturer and system generation, and some equipment exposes limited data. We verify what your specific configuration supports during discovery rather than assuming a level of access that may not exist.
We instrument drift detection, track performance by equipment and protocol, and monitor subgroup results for fairness. Monitoring includes defined thresholds and rollback triggers. Revalidation cadence is agreed during scoping, and retraining is handled as a controlled, documented change rather than a silent model swap.
Yes, subject to governance approval and appropriate agreements. We work with de-identified datasets, document provenance, and establish annotation protocols with your interventionalists. Data volume and annotation quality usually determine feasibility more than model architecture, which is why discovery includes a candid data readiness assessment.