JSON twin: https://www.healthaidb.com/software/pixelshine.json
AlgoMedica
https://algomedica.com/low-radation-ct-scans-algomedica
PixelShine is a deep-learning CT post-processing software that denoises low-dose CT images to improve image quality and enable reduced radiation protocols.
PixelShine (AlgoMedica) is a vendor-agnostic deep-learning-based image denoising/post-processing tool for CT. It accepts DICOM CT input and outputs enhanced DICOM images, integrates with PACS/reading environments or runs as a stand‑alone/hybrid deployment (local VM, dedicated hardware), and is intended to improve low-dose CT image quality across multiple body regions. Regulatory clearances include CE (MDD, Class IIa) and FDA 510(k) (Class II).
unknown
2012
P2011
2025-09-07
commercial proprietary (vendor-licensed); FDA 510(k) cleared; CE MDD Class IIa
One-off purchase or subscription options; pricing based on number of analyses, installations or licensed CT scanners; contact vendor for pricing and trials.
subscription
—
2019
Hospital network connectivity, PACS/DICOM connectivity, server-class hardware (on-prem), DICOM storage and routing configured
product
1.0
{
"company_name": "AlgoMedica",
"company_url": "https://algomedica.com/",
"company_offices": [
"United States"
],
"company_founding": "2012",
"product_url": "https://algomedica.com/low-radation-ct-scans-algomedica",
"categories": [
"clinical",
"diagnostic",
"imaging",
"radiology",
"AI/machine learning",
"post-processing"
],
"market_segment": [
"enterprise",
"smb"
],
"links": [
"https://algomedica.com/",
"https://algomedica.com/low-radation-ct-scans-algomedica",
"https://algomedica.com/about",
"https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm?ID=K161625",
"https://www.accessdata.fda.gov/cdrh_docs/pdf16/K161625.pdf",
"https://radiology.healthairegister.com/products/algomedica-pixelshine",
"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10969114/",
"https://asset.fujifilm.com/www/uk/files/2021-05/1f64fbb72811e1afea76c4fbc618bb19/Pixel_Shine.pdf"
],
"summary": "PixelShine is a deep-learning CT post-processing software that denoises low-dose CT images to improve image quality and enable reduced radiation protocols.",
"description": "PixelShine (AlgoMedica) is a vendor-agnostic deep-learning-based image denoising/post-processing tool for CT. It accepts DICOM CT input and outputs enhanced DICOM images, integrates with PACS/reading environments or runs as a stand‑alone/hybrid deployment (local VM, dedicated hardware), and is intended to improve low-dose CT image quality across multiple body regions. Regulatory clearances include CE (MDD, Class IIa) and FDA 510(k) (Class II).",
"target_users": [
"radiologists",
"radiology technologists",
"PACS administrators",
"medical physicists",
"imaging IT/engineers",
"hospital administrators"
],
"specialties": [
"Abdomen",
"Cardiac",
"Chest",
"Musculoskeletal",
"Neuro",
"Vascular"
],
"regions_available": [],
"languages_supported": [],
"pricing_model": "subscription",
"pricing_details": "One-off purchase or subscription options; pricing based on number of analyses, installations or licensed CT scanners; contact vendor for pricing and trials.",
"license": "commercial proprietary (vendor-licensed); FDA 510(k) cleared; CE MDD Class IIa",
"deployment_model": [
"on_prem"
],
"os_platforms": [
"Linux",
"Windows"
],
"features": [
"Deep-learning CT image denoising (noise reduction)",
"Enables low-dose / ultra-low-dose CT protocols",
"Processes DICOM CT studies and returns enhanced DICOM",
"Vendor-agnostic support for any CT scanner meeting minimum functional requirements",
"Integration with PACS workflow (automatic send/receive)",
"Preserves thin-slice reconstructions",
"Rapid/real-time post-processing for clinical workflow",
"Supports pediatric, lung screening, obese patient, cardiac and neuro CT use cases",
"Maintains natural appearance (avoids waxy IR look)",
"Improves signal-to-noise ratio (SNR) and edge definition"
],
"optional_modules": [],
"integrations": [
"PACS",
"CT scanners (vendor-agnostic)",
"RIS",
"VNA",
"DICOM modalities/AE titles"
],
"data_standards": [
"DICOM",
"DICOMweb",
"HL7 v2"
],
"api_available": "unknown",
"system_requirements": "Hospital network connectivity, PACS/DICOM connectivity, server-class hardware (on-prem), DICOM storage and routing configured",
"compliance": [
"FDA 510(k) cleared (K161625)",
"HIPAA"
],
"certifications": [
"FDA 510(k) (K161625)"
],
"security_features": [
"Network encryption (DICOM over TLS likely)",
"Role-based access control (RBAC)",
"Audit logging"
],
"privacy_features": [
"BAA available"
],
"data_residency": "",
"customers": [
"University of Virginia Health System",
"Palo Alto Medical Clinic",
"University of Alabama at Birmingham (UAB) - Dept. of Radiology",
"CT Protocols LLC (S. Singh associated endorsement)"
],
"user_reviews": [
"High quality images without the blurring; more natural look CT image; processes a typical study in less than a minute; dedicated hardware is not required. (Fujifilm product page)",
"PixelShine uses deep-learning algorithms to reduce noise from CT scans, allowing clinicians to obtain high-quality scans at very low radiation doses. (AuntMinnie coverage)",
"Improves image quality and diagnostic confidence in low‑dose and ultra‑low‑dose CT studies. (peer‑reviewed studies summary)",
"May enable reduced radiation dose while maintaining or improving detectability of subtle pathologies. (Health AI Register summary)"
],
"ratings": [
"FDA: 510(k) cleared (Class II) - listed by Health AI Register",
"CE: MDD (Class IIa) - listed by Health AI Register",
"On market since May 2019 - market presence noted by Health AI Register",
"Peer‑reviewed studies reporting improved image quality (NIH / PMC publications)"
],
"support_channels": [
"email",
"phone (via distributors/resellers)",
"distributor/reseller support",
"request-a-demo/contact form"
],
"training_options": [
"documentation (online resources / case studies)",
"video tutorials / video gallery",
"webinars",
"on-site installation / distributor-led onboarding"
],
"release_year": "2019",
"integration_partners": [
"Fujifilm (FCT PixelShine collaborations/integration)",
"InferVision (commercial partnership announced)",
"Romion Health (Health AI Register / marketplace listing)",
"PACS vendors (standard PACS integration - generic vendor integration)",
"AI marketplaces / distribution platforms (unnamed marketplaces referenced)",
"Distributor / reseller partners (e.g., Oncology Systems referenced as reseller)"
],
"id": "P2011",
"slug": "pixelshine",
"type": "product",
"version": "1.0",
"last_updated": "2025-09-07",
"links_json": {
"self": "https://www.healthaidb.com/software/pixelshine.json"
}
}