Find the artificial intelligence based software for radiology that you are looking for. All products listed are available for the European market (CE marked).
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Subspeciality: Neuro
Modality: MR
Source: Vendor
Best neuropsychological predictors, Best voxel-based map predictors overlayed on the subject gray matter, Cognitive, Functional and behavioral deficits of the subject, Mild cognitive impairment (MCI) subject risk score (low risk vs high risk) of being affected by or progressing to Alzheimer's disease dementia within 24 months, Subject gray matter volume and images with normative comparison
TRACE4AD provides the subject's level of risk (low or high risk) of having or progressing to Alzheimer's disease dementia within 24 months, by an automatic reading of the subject's brain gray matter obtained from a 3D structural T1-weighted MRI brain study, also in combination with subject's neuropsychological measures.
Subspeciality: Abdomen
Modality: Ultrasound
Source: Vendor
Classification of risk of having ovarian cancer
TRACE4OC provides the woman's level of risk (very low risk or medium-high risk) of being affected with ovarian cancer at the date of the TRACE4OC-processed USI investigation of an adnexal mass, combined with the serum level test for Cancer Antigen 125 (CA-125), performed no earlier than and no later than one month from the USI study, and with the current woman's menopausal state (premenopausal or post menopause).
Subspeciality: Neuro
Modality: MR
Source: Vendor
Atrophy and white matter lessions identification, Brain roi segmentation, Longitudinal analysis, Normative comparison, Number and clasification of lesions, White and grey matter quantification
Neurocloud VOL provides volumetric analysis for atrophy and lesion quantification in MRI. It assists in the follow-up and evolution of neurodegenerative pathologies.
- MRI T1: identifies atrophy in the patient's brain. Clinically relevant brain structures are segmented and volumetric data from the patient's brain is compared with the normality distribution.
- FLAIR: identifies inflammatory lesions and hyperintense regions in white matter, and presents results in graphics and images for both the evolution of the atrophy and the growth/decrease of the lesions and the appearance of new lesions.
Subspeciality: Neuro
Modality: MR, SPECT
Source: Vendor
Automatic co-registration SPECT-MRI, Identification of epileptogenic focus, Interictal spect subtraction ictal image, Percentage overlap of the focus
Automatic co-registration of the SPECT images with the patient's MRI. Interictal SPECT image subtraction is applied on the ictal image and the epileptogenic zone is identified. The SISCOM procedure is recommended by the EANM in the study of epilepsy, and provides high sensitivity and specificity in the localization of the epileptogenic focus. Neurocloud SISCOM provides a parametric map of the voxels identified as epileptogenic zone on MRI, data tables with the maximum Z-Score for each region of interest (ROI) as well as the percentage overlap of the focus and the SPECT - MRI fusion image.
Subspeciality: Neuro
Modality: MR, PET
Source: Vendor
Customizable report, Identify and quantify regions with abnormal metabolism, Positive/negative amyloid result
Neurocloud PET for quantitative brain PET image analysis provides neurology and nuclear medicine professionals with automatic assistance in the diagnosis and monitoring of neurodegenerative diseases. - FDG PET imaging: identifies regions with abnormal metabolism by comparative analysis against an extensive database of normals, stratified by age. An analysis based on regions of interest, asymmetries and parametric statistical analysis (voxel by voxel) is performed. - Amyloid PET imaging: provides SUVR values and outcome (amyloid positive/negative) compared to validated thresholds.
Subspeciality: Cardiac
Modality: MR
Source: Vendor
CE
FDA
And ejection fraction, Heart ventricles segmentation, Myocardial mass, Quantification of ventricular volumes, Wall motion classification
The AI4CMR software performs a automatic cardiac segmentation and interpretation of Cardiac Magnetic Resonance (CMR), allowing quantification of various parameters without the need for intervention by a medical professional.
It automatically identifies cases with normal left and right ventricle wall motion (regional contractility), aimed at increasing awareness for the cases with suspicious wall motion abnormalities to the reporting physicians.
AIRAmed
Subspeciality: Neuro
Modality: MR
Source: Vendor
Brain tissue and anatomy segmentation, Normative comparison, Report generation, Volume quantification, WMH detection and quantification
AIRAscore structure provides quantitative data of brain tissue and brain structures for early detection of atrophies and tracking progression. In addition, the lesion characterisation and quantification may support the diagnosis of a wide range of neurodegenerative diseases. The results are presented in the PACS as a PDF report and compared to an age- and sex-correlated reference collective. Bar charts and a pictogram-based spatial representation of the results facilitate their interpretation.
Subspeciality: Spine
Modality: MR
Source: Vendor
Editable report, Editable separate pathology report, Lumbar spine annotation, Measurement calculation based on segmentation, Smart navigation
CoLumbo is an AI assistant software for the interpretation of lumbar spine MR scans. It is a deep learning algorithm that aims to help radiologists reduce the patient examination reading and reporting time, and increase the accuracy of measurements, and facilitate standardization in spine MRI reporting and increase the patient – physician communication and trust.
Subspeciality: Multiple
Modality: CT
Source: Vendor
CE
FDA
Noise reduction of low dose CT
PixelShine is an algorithm for de-noising CT datasets supporting new CT protocols to drive patient dose down, while image quality is maintained. PixelShine may aid detectability of subtle pathologies which are borderline visible. The applications apply to CT without limit whether Filtered Back projection (FBP) and Iterative Reconstruction (IR).
Subspeciality: Chest
Modality: X-ray
Source: Vendor
Automated cardiothoracic ratio, Bone subtraction, Bone suppression, COVID-19 score, Detection of 148 chest findings grouped into 17 classes
Rayscape CXR solution identifies a total of 148 findings on chest x-rays that are further on grouped into 17 main classes.The Rayscape's algorithms show their location on the x-ray scan and provide doctors with additional information such as the CTR index and bone suppressed and subtracted versions of the medical image and a COVID 19 score. *The company was previously named XVision, and the product CheXVision
Subspeciality: Neuro
Modality: CT
Source: Vendor
Confidence bar, Detection of up to 130 findings (acute and chronic) on brain CT, Normal/abnormal differentiation, Notification, Visualisation, Worklist triage
Harrison.ai CT Brain is an AI clinical decision-support solution for non-contrast head CT, detecting up to 130 findings. Features include: • customisable, interactive viewer that integrates into PACS/RIS • a confidence bar displaying the likelihood of the finding and uncertainty of the AI model • worklist triage.
Subspeciality: Chest
Modality: X-ray
Source: Vendor
Confidence bar, Detection of up to 124 chest findings + detection of suspected tuberculosis, Normal/abnormal differentiation, Notification, Worklist triage
Harrison.ai Chest X-Ray is an AI clinical decision-support solution for chest X-ray, assisting clinicians to interpret chest X-Rays studies by detecting up to 124 findings + suspected tuberculosis. It acts as a second pair of eyes providing notification of suspected findings. Features include: • analysing up to three images per study including frontal and lateral images • a confidence bar displaying the likelihood of the finding and uncertainty of the AI model • customisable user interface that integrates seamlessly into PACS and RIS. • worklist triage