Neurophet AQUA is a software tool that helps clinicians and researchers analyze brain MRI scans by automatically identifying and measuring brain structures. It generates detailed reports comparing patient brain volumes to reference data, aiding in the assessment of neurological conditions and monitoring structural brain changes.
The Lumify Diagnostic Ultrasound System by Philips Ultrasound is a transportable ultrasound device that provides high-resolution diagnostic imaging across various modes including B-mode, Doppler, and M-mode. It incorporates an AI-based software feature that automatically detects and quantifies lung B-lines and merged B-lines from ultrasound videos to assist clinicians in assessing lung conditions such as pneumonia and pulmonary edema. The system supports multiple transducers and is designed for use by healthcare professionals in diverse clinical settings.
Auto Segmentation by GE Medical Systems is an AI software tool that automatically generates organ-at-risk contours from CT scans to help radiation oncologists, medical physicists, and dosimetrists speed up radiation therapy planning. It produces initial segmentation contours that users can review and adjust, improving workflow efficiency and precision in radiation treatment.
The SIS System is a software tool that uses advanced machine learning and image processing to help surgeons, neurologists, and radiologists visualize critical brain structures in 3D. It assists in planning neurological procedures such as Deep Brain Stimulation by creating detailed anatomical models from MRI images and localizing implanted leads on post-operative CT images, improving accuracy and surgical outcomes.
ENT EM is a surgical navigation system designed to assist surgeons during ear, nose, and throat procedures by providing real-time guidance using electromagnetic tracking. It integrates with patient imaging data from multiple modalities to accurately localize instruments and anatomical structures, improving surgical precision and safety. The device includes an AI/ML-based algorithm to aid in the registration step by automatically detecting anatomical landmarks, streamlining the planning and navigation process.
Precision DL by GE Healthcare is a deep learning software designed to improve the quality of non-Time-of-Flight PET images used in clinical oncology. It enhances image contrast and reduces noise, helping clinicians obtain clearer PET scans to better detect and evaluate cancer, ultimately supporting improved patient care.
MR DWI/FLAIR Measurement V1.0 is a medical image processing software developed by Olea Medical that analyzes MRI brain images from diffusion-weighted imaging (DWI) and fluid-attenuated inversion recovery (FLAIR) sequences. It automatically computes diffusion maps and extracts relevant metrics to assist medical professionals in evaluating brain conditions. The software integrates with existing medical imaging platforms and helps clinicians by providing quantitative analysis to complement their diagnosis and treatment planning.
The iCAC Device is a software tool that analyzes routine chest CT scans to automatically detect and quantify coronary artery calcium, which helps physicians assess cardiovascular risk. It provides outputs such as calcium segmentation visualizations and quantitative calcium scores during standard clinical workflows, assisting physicians without replacing original reports or scans.
Ceevra Reveal 3 is a software medical device designed for processing, reviewing, and analyzing 3D images created from CT and MR scans. It helps clinicians with preoperative surgical planning and intraoperative image display, including interacting with 3D visualizations using mobile or desktop viewers, and even VR headsets. By using AI-driven algorithms, it generates preliminary segmentations of normal anatomical structures to assist healthcare professionals in their clinical decisions for adult patients.
ViewFinder Software Version 1.1 by Elaitra Ltd is a specialized software tool designed for clinicians to review digital breast tomosynthesis images. It dynamically matches tissue across different breast views using AI to reduce cognitive load, helping radiologists to compare images more efficiently and accurately during breast cancer screening and diagnosis.
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