Change Healthcare Anatomical AI
by Change Healthcare
· Based in United States →
— Provider of innovative technology and business solutions to improve the healthcare journey for providers, payers, partners and patients.
Regulatory Status Disclosed
Overview
Change Healthcare Anatomical AI is a standalone image processing software application designed to analyze pixel data from CT or MR images. It generates comprehensive anatomic descriptors, which supplement traditional methods used for the selection, presentation, or analysis of image-based medical data. This AI tool is intended to enable physicians and other healthcare providers, as well as integrated healthcare systems, to rapidly identify images, series, and/or studies of interest. By automating the identification of body regions using image pixel data, it aims to remove barriers caused by inaccurate or incomplete metadata, thereby eliminating time spent on manual study searches and potentially reducing the ordering of unnecessary studies.
Reviewed by Pouyan Golshani, MD — Interventional Radiologist
Key Features
- Analyzes pixel data from CT or MR images
- Creates comprehensive anatomic descriptors
- Supplements traditional image analysis methods
- Rapidly identifies relevant images, series, and studies
- Eliminates time spent on manual study searches
- Helps reduce the ordering of unnecessary studies
- Available in on-premise Change Healthcare Radiology Solutions (PACS)
- Planned integration into Stratus Imaging cloud solution suite
- Communicates via Application Programmable Interfaces (APIs)
- Exports inference results, typically in JSON format
Use Cases
- Improving radiology workflow efficiency
- Streamlining study prioritization
- Enhancing diagnostic confidence
- Reducing manual image search times
- Categorizing anatomy from patient images, series, or studies
- Integration with existing Picture Archiving and Communication Systems (PACS) and Electronic Health Records (EHR)
What Physicians Need to Know
DICOM Support & Standards
Change Healthcare Anatomical AI is a standalone image processing software application that analyzes CT and MR DICOM images. It adheres to NEMA PS 3.1-3.20 (2016) – Digital Imaging and Communications in Medicine (DICOM) set. The device communicates via Application Programmable Interfaces (APIs) which allow for receiving DICOM images and returning inference results. The algorithm produces a JSON file containing analysis results for each image and study with identified body regions.
PACS Integration Method
Change Healthcare Anatomical AI is currently available in Change Healthcare Radiology Solutions (PACS) for hospitals and will be added to future releases in its Stratus Imaging cloud solution suite. It integrates with Change Healthcare PACS to provide an efficient workflow for creating cases. The processed images go directly into a hospital's existing imaging system, rather than requiring a separate destination for review.
Reading Room Workflow Impact
The application is intended to enable physicians and other healthcare providers to rapidly identify images, series, and/or studies of interest. It works in parallel to and in conjunction with the standard of care workflow and does not alter the original medical image. The anatomical descriptors generated are used as supplemental metadata for a patient's imaging study. AI in general can help automate time-consuming tasks like reviewing medical images, allowing healthcare professionals to focus more on direct patient care.
AI Model Architecture (deep learning approach)
The algorithm analyzes CT or MR image pixel data and generates anatomical descriptors. Deep learning models are highly effective in analyzing medical images, detecting abnormalities, prioritizing critical cases, and reducing diagnostic errors. Deep learning with reasoning based on anatomical knowledge can enable models to remain robust in the presence of metal implants, imaging artifacts, and anatomical variations.
Processing Speed (per study)
AI systems can analyze thousands of data points in a few seconds, a task that might take a human expert several hours or even days. In one comparison, an AI algorithm reviewed X-rays in 90 seconds, while board-certified radiologists took four hours for the same task.
FDA Clearance Pathway (510k/De Novo)
Change Healthcare Anatomical AI received FDA 510(k) clearance (K210719) on July 20, 2021. It was classified as a Class II device under regulation number 21 CFR 892.2050, with product code QIH (Automated Radiological Image Processing Software). The device was found substantially equivalent to the AquariusAPS Server (K061214).
Supported Modalities (CT/MRI/X-ray/US)
Change Healthcare Anatomical AI is intended to analyze pixel data from CT or MR images.
Sensitivity & Specificity Data
AI-assisted healthcare professionals have shown significantly greater sensitivity and specificity compared to unassisted healthcare professionals. Deep learning models have performed as well as healthcare professionals in diagnosing diseases using medical imaging.
Physician Tip
Change Healthcare Anatomical AI can help streamline image review by rapidly identifying and categorizing anatomical regions in CT and MR scans, acting as supplemental metadata. This can potentially reduce the time spent on initial image sorting and organization, allowing for a more focused review of relevant studies. However, it's crucial to remember that the AI provides supplementary information and does not alter the original medical image, maintaining the physician's central role in diagnosis. It's important to understand how the AI integrates into your existing PACS workflow to maximize its efficiency benefits.
The Change Healthcare Anatomical AI is designed for integration with existing healthcare systems, particularly Change Healthcare's Radiology Solutions PACS and future Stratus Imaging cloud solution suite. It uses APIs to receive DICOM images and return analysis results in a JSON file format, facilitating its incorporation into integrated applications for categorizing anatomy. This allows for a seamless flow of information within the radiology workflow without requiring a separate review destination.
Details
| Category | Radiology & Imaging AI |
| Pricing | Unknown |
| Deployment | Cloud-based and on-premise. It is available in Change Healthcare Radiology Solutions (PACS) for hospitals and will be added to future releases in its Stratus Imaging cloud solution suite. |
| API Available | Unknown |
| Data Export | Unknown |
| Compliance | |
| BAA Available | Yes AI-estimated |
| HIPAA Compliant | Yes AI-estimated |
| FDA Status | Yes AI-estimated |
| Integrations | |
| EHR | Not specified |
| Specialties | Radiology |
What the Web Says
Change Healthcare Anatomical AI is a standalone image processing software that analyzes CT and MR DICOM images to create comprehensive anatomic descriptors for integrated healthcare systems. It aims to supplement traditional methods for image-based medical data analysis and help physicians and healthcare providers rapidly identify images of interest. The AI models are trained using clinical data and honed by expert physicians to extract diagnostic information from EHRs, which can improve the efficiency of automated medical necessity reviews.
Overall: MixedStrengths
- Analyzes CT and MR images to create comprehensive anatomic descriptors.
- Supplements traditional methods for image-based medical data analysis.
- Helps physicians and healthcare providers rapidly identify images, series, and studies of interest.
- Trained by expert physicians using clinical data.
- Extracts meaningful diagnostic information from text in EHRs.
- Increases efficiency of automated medical necessity reviews by over 20%.
Limitations
- Not indicated for patients under 18 years old.
- No specific reviews for "Change Healthcare Anatomical AI" were found on G2, Capterra, or Reddit, making it difficult to assess user-reported cons directly related to this specific product.
- General concerns about AI in healthcare include potential for bias in AI models, data privacy issues, and the need for human oversight.
Based on reviews from: capterra.com, reddit.com, fda.gov, g2.com, itnonline.com, unite.ai, chiefhealthcareexecutive.com, healthcareitnews.com, illinois.edu, hitconsultant.net, trustpilot.com, indeed.com, businesswire.com, medicalrecords.com
Last updated: 2026-10-29
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Press & Coverage
businesswire.com
Change Healthcare Expands Functionality and Drives Industry Transition to Cloud-Based Imaging and Storage
Change Healthcare's Enterprise Imaging division has received its first FDA clearance for its Anatomical AI algorithm, which is designed to improve workflow efficiency by identifying body regions using image pixel data. This algorithm is currently available in their on-premise Radiology Solutions (PACS) and will be integrated into future releases of their Stratus Imaging cloud solution suite. The company is consolidating its cloud-native enterprise imaging solutions under the new Change Healthcare Stratus Imaging category.
2021-08
orthogonal.io
SaMD Cleared by the FDA: The Ultimate Running List
This article provides a comprehensive list of Software as a Medical Device (SaMD) cleared by the FDA, including Change Healthcare Anatomical AI, which received clearance on July 20, 2021, for radiology applications. The data for this list is compiled from publicly available sources such as archived FDA reports and regulatory search tools.
2024-10
fda.gov
Change Healthcare Anatomical AI
The FDA cleared Change Healthcare Anatomical AI on July 20, 2021, as a standalone image processing software application. It is intended to analyze pixel data from CT or MR images to create comprehensive anatomic descriptors for export to integrated healthcare systems, supplementing traditional methods for image data selection, presentation, or analysis.
2021-07
axisimagingnews.com
AI in Radiology: 6 Things to Consider for a Successful Cloud Migration
Change Healthcare Anatomical AI is presented as a cloud-based platform utilizing machine learning algorithms to assist radiologists in efficiently locating relevant images by identifying body regions from image pixel data. This eliminates issues caused by inaccurate or incomplete metadata, thereby reducing manual search times and preventing unnecessary scans.
2023-06
nih.gov
FDA-Cleared AI Algorithms Relevant to Abdominal Imaging
This review of FDA-cleared AI algorithms for abdominal imaging mentions Change Healthcare Anatomical AI, cleared on July 20, 2021, as an algorithm that provides anatomical region matching with images. It highlights how AI algorithms like Anatomical AI can be embedded in radiology IT systems to supplement workflows and improve efficiency.
2025-06
nih.gov
Opportunistic Screening on Chest CT: A Review of Imaging Biomarkers and the Role of Artificial Intelligence
This peer-reviewed article discusses the potential of AI in opportunistic screening on chest CT, listing Change Healthcare Anatomical AI (K210719, 07/20/2021) as an example of an AI tool for matching anatomic regions with images. The article emphasizes how AI can address workflow and reproducibility issues in deriving imaging biomarkers from CT scans.
2025-07
healthcareaiops.com
Change Healthcare Anatomical AI
Change Healthcare Anatomical AI received FDA 510(k) clearance (K210719) on July 20, 2021. This entry in an AI software database confirms its regulatory status and provides basic information about the product.
2026-08
Videos
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Frequently Asked Questions
Change Healthcare Anatomical AI is designed to analyze pixel data from CT or MR images to create comprehensive anatomic descriptors. This supplements traditional methods for image data analysis, helping physicians and other healthcare providers to quickly identify images, series, and studies of interest. The AI works in parallel with standard workflows and does not alter the original medical image.
Change Healthcare Anatomical AI adheres to cybersecurity requirements outlined by the FDA Guidance for 'Content of Premarket Submissions for Management for Cybersecurity in Medical Devices,' implementing controls to protect data in use, in transit, or at rest. It received FDA 510(k) clearance in 2021 under product code QIH. When deploying AI in healthcare, it's crucial to ensure HIPAA compliance, including formal risk analysis, secure data handling through Business Associate Agreements, and robust administrative, physical, and technical safeguards.
Change Healthcare Anatomical AI is not indicated for patients under 18 years old. More broadly, AI in healthcare, including in radiology, has limitations such as potential for bias in algorithms if historical data is biased, and the inability to replicate human intuition, empathy, or the nuanced judgment required for complex cases. While AI can assist with workflow and identify patterns, human radiologists are still needed for the majority of image interpretation, clinical context, and accurate decision-making.
While specific direct alternatives to Change Healthcare Anatomical AI's precise function of generating anatomical descriptors from CT/MR images are not explicitly detailed, the broader market for healthcare AI and imaging solutions includes numerous companies. Change Healthcare itself offers a wide range of healthcare technology solutions, and alternatives for various healthcare IT services include companies like Allscripts/Veradigm, Elation Health, Experity, ModMed, Infinx, and others. Many AI tools are emerging in radiology to help sort data, organize exams, and prioritize scans.
Specific pricing for Change Healthcare Anatomical AI is not publicly available and typically requires a direct quote based on requirements. In general, pricing for clinical AI tools varies widely, from free tiers to enterprise contracts that can be substantial. Some AI solutions are funded by institutions, making them free at the point of use for clinicians, while others have published subscription models or require sales-led discussions for pricing.
Change Healthcare Anatomical AI is currently available in its on-premise Change Healthcare Radiology Solutions (PACS) for hospitals. The system communicates via Application Programmable Interfaces (APIs) to receive DICOM images and return analysis results in a JSON file, which contains identified body regions for each image and study. This allows the derived anatomical descriptors to be exported to integrated healthcare systems as supplemental metadata.
No, Change Healthcare Anatomical AI is intended to supplement, rather than replace, the expertise of human radiologists. AI in radiology helps organize images, prioritize urgent cases, and improve workflow, but it cannot replace the judgment, communication, and patient-care skills of trained professionals. The majority of image interpretation still relies on human radiologists to review images, understand clinical context, and ensure accurate patient care.
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| Last Verified: 2026-04-18 | First Added: 2026-04-18
Investors who backed Change Healthcare Anatomical AI
Funded through the company that built this tool.
