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ProductsAmCAD-UT®

Vendor source

Reviewed 3 Jul 2026

Completeness Strong (78%)

AmCAD-UT®

AmCad BioMed

AmCAD-UT® Detection gives physicians a tool to process ultrasound images for sonographic characteristics that assist in making diagnostic decisions. AmCAD-UT® Detection uses statistical pattern recognition and quantification methods to perform analytical processing of images. By processing the image for key characteristics (i.e., echogenic foci, echogenicity, texture, margin, anechoic areas, height/width ratio, nodule shape, and nodule size). AmCAD-UT® Detection provides physicians with quantification and visualization of the sonographic characteristics for informed decision making.

Supported by 5 papers

AmCAD-UT®
AmCAD-UT®
AmCAD-UT®
AmCAD-UT®
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Key Features

  • Automated nodule recognition
  • Quantification and visualization of sonographic features
  • Risk analysis based on global guidelines

General Information

Product name

AmCAD-UT®

Modality

Ultrasound

Main task

Not specified

Subspeciality

Thyroid

Disease targeted

Thyroid cancer, Thyroid nodule

Regulatory Information

CE Certification

Pathway:

MDD

Class:

Class IIa

Verified by Health AI Register

FDA Certification

Pathway:

510(k) cleared

Class:

Class II

Verified by Health AI Register

Other certifications

Not specified

Evidence & Research

Peer-Reviewed Papers

Application of AmCAD‐UT in Active Surveillance of Papillary Thyroid Microcarcinoma and Suspicious Subcentimeter Thyroid Nodules: A Prospective Agreement Study

World Journal of Surgery · May 2026

Computer‐Aided Diagnosis in the Evaluation of Thyroid Nodules: A Study of Intra‐ And Inter‐Rater Reliability and Agreement

Head & Neck · Apr 2026

Improving the diagnostic strategy for thyroid nodules: a combination of artificial intelligence-based computer-aided diagnosis system and shear wave elastography

Endocrine · Oct 2024

Multi-Reader Multi-Case Study for Performance Evaluation of High-Risk Thyroid Ultrasound with Computer-Aided Detection

Cancers · Feb 2020

Diagnostic Performance Evaluation of a Computer-Assisted Imaging Analysis System for Ultrasound Risk Stratification of Thyroid Nodules

American Journal of Roentgenology · Apr 2019

Technical Specifications

Patient population age

Not specified

Input

2D grayscale ultrasound images

Input format

BMP, DICOM, JPEG or TIFF

Output

Visualized and quantified sonographic features, recommendation based on TI-RADS and global guidelines including AACE/ACE/AME, ACR , ATA, EU-TIRADS, BTA, Kwak et al., KSThR and KSR, ) and Seo et al.

Output format

DICOM, PDF

Integration

Integration in standard reading environment (PACS), Integration via AI marketplace or distribution platform, Stand-alone webbased

Deployment

Cloud-based, Locally on dedicated hardware

Trigger for analysis

Automatically, right after the image acquisition, On demand, triggered by a user through e.g. a button click, image upload

Processing time

< 10 seconds

Population

Thyroid ultrasound scanning for thyroid nodule

Market Presence

On market since

2017

AI Platforms

Resellers

Not specified

Countries present

13

Paying clinical customers

4 countries

Research/test users

12 countries

Pricing Information

Pricing model

Subscription

Based on

Number of analyses, Number of installations

Source: Vendor | First published: Jul 10, 2025 | Last updated: Jul 3, 2026