Search Results

Lung-CAD is a computer-assisted detection (CADe) software device that analyzes chest radiograph studies for lung hyperinflation. The device uses a deep learning algorithm to identify regions of interest (ROIs) with lung hyperinflation and produces boxes around the ROIs. Lung-CAD is intended for use as a concurrent reading aid for physicians interpreting chest X-rays. The device is not intended for clinical diagnosis of any disease. It does not replace the role of other diagnostic testing in the standard of care for lung parenchymal findings. Lung-CAD is indicated for adults only.

Lung-CAD is computer-assisted detection (CADe) software designed to increase the accurate detection of lung hyperinflation. Lung-CAD's output is available for physicians interpreting chest radiographs as a concurrent reading aid. The device helps physicians more effectively identify lung hyperinflation. Lung-CAD does not replace the role of the physician or of other diagnostic testing in the standard of care and does not provide a diagnosis for any disease. Lung-CAD uses modern deep learning and computer vision techniques to analyze chest radiographs. For each image within a study, Lung-CAD generates a DICOM Presentation State file (output overlay). If any region of interest (ROI) is detected by Lung-CAD in the study, the output overlay for each image includes "Lung hyperinflation". In addition, if ROI(s) are detected in an image, bounding boxes surrounding each detected ROI are included in the output overlay for that image and are labeled with the radiographic findings: "Lung hyperinflation". If no ROI is detected by Lung-CAD in the study, the output overlay for each image will include the text "No Lung-CAD ROI(s)" and no bounding boxes will be included. Regardless of whether an ROI is detected, the overlay includes text identifying the X-ray study as analyzed by Lung-CAD and a customer configurable message containing a link or instructions, for users, to access labeling documents. The Lung-CAD overlay can be toggled on or off by the physician within their Picture Archiving and Communication System (PACS) viewer, allowing for concurrent review of the X-ray study.

Lung-CAD is a computer-assisted detection (CADe) software device that analyzes chest radiograph studies for interstitial thickening. The device uses a deep learning algorithm to identify regions of interstital thickening and produces boxes around the ROIs. Lung-CAD is intended for use as a concurrent reading aid for physicians interpreting chest X-rays. The device is not intended for clinical diagnosis of any disease. It does not replace the role of other diagnostic testing in the standard of care for lung parenchymal findings. Lung-CAD is indicated for adults only.

Lung-CAD is computer-assisted detection (CADe) software designed to increase the accurate detection of interstitial thickening. Lung-CAD's output is available for physicians interpreting chest radiographs as a concurrent reading aid. The device helps physicians more effectively identify interstitial thickening. Lung-CAD does not replace the role of the physician or of other diagnostic testing in the standard of care and does not provide a diagnosis for any disease. Lung-CAD uses modern deep learning and computer vision techniques to analyze chest radiographs. For each image within a study, Lung-CAD generates a DICOM Presentation State file (output overlay). If any ROI is detected by Lung-CAD in the study, the output overlay for each image includes "Interstitial thickening". In addition, if ROI(s) are detected in an image, bounding boxes surrounding each detected ROI are included in the output overlay for that image and are labeled with the radiographic finding: "Interstitial thickening". If no ROI is detected by Lung-CAD in the study, the output overlay for each image will include the text "No Lung-CAD ROI(s)" and no bounding boxes will be included. Regardless of whether an ROI is detected, the overlay includes text identifying the X-ray study as analyzed by Lung-CAD and a customer configurable message containing a link or instructions, for users, to access labeling documents. The Lung-CAD overlay can be toggled on or off by the physician within their Picture Archiving and Communication System (PACS) viewer, allowing for concurrent review of the X-ray study.

Aorta-CAD is a computer-assisted detection (CADe) software device that analyzes chest radiograph studies for suspicious regions of interest (ROIs). The device uses a deep learning algorithm to identify ROIs and produces boxes around the ROls. The boxes are labeled with one of the following radiographic findings: Aortic calcification or Dilated aorta. Aorta-CAD is intended for use as a concurrent reading aid for physicians looking for ROIs with radiographic findings suggestive of Aortic Atherosclerosis or Aortic Ectasia. It does not replace the role of the physician or of other diagnosic testing in the standard of care. Aorta-CAD is indicated for adults only.

Aorta-CAD is computer-assisted detection (CADe) software designed for physicians to increase the accurate detection of findings on chest radiographs that are suggestive of chronic conditions in the aorta. The ROIs are labeled with one of the following radiographic findings: Aortic calcification or Dilated aorta. Aorta-CAD is intended for use as a concurrent reading aid for physicians looking for suspicious ROIs with radiographic findings suggestive of Aortic Atherosclerosis or Aortic Ectasia. Aorta-CAD's output is available for physicians as a concurrent reading aid and does not replace the role of the physician or of other diagnostic testing in the standard of care for the distinct conditions. Aorta-CAD uses modern deep learning and computer vision techniques to analyze chest radiographs. For each image within a study, Aorta-CAD generates a DICOM Presentation State file (output overlay). If any ROI is detected by Aorta-CAD in the study, the output overlay for each image includes which radiographic finding(s) were identified and what chronic condition in the aorta is suggested by these findings, such as "Aortic calcification suggestive of Aortic Atherosclerosis." In addition, if ROI(s) are detected in an image, bounding boxes surrounding each detected ROI are included in the output overlay for that image and are labeled with the radiographic findings, such as "Aortic calcification". If no ROI is detected by Aorta-CAD in the study, the output overlay for each image will include the text "No Aorta-CAD ROI(s)" and no bounding boxes will be included. Regardless of whether an ROI is detected, the overlay includes text identifying the X-ray study as analyzed by Aorta-CAD and a customer configurable message containing a link to our instructions for users to access labeling documents. The Aorta-CAD overlay can be toggled on or off by the physician within their Picture Archiving and Communication System (PACS) viewer, allowing for concurrent review of the X-ray study.

Chest-CAD is a computer-assisted detection (CADe) software device that analyzes chest radiograph studies using machine learning techniques to identify, categorize, and highlight suspicious regions of interest (ROI). Any suspicious ROI identified by Chest-CAD is assigned to one of the following categories: Cardiac, Mediastinum/Hila, Lungs, Pleura, Bones, Soft Tissues, Hardware, or Other. The device is intended for use as a concurrent reading aid for physicians. Chest-CAD is indicated for adults only.

Chest-CAD is a computer-assisted detection (CADe) software device designed to assist physicians in identifying suspicious regions of interest (ROIs) in adult chest X-rays. Suspicious ROIs identified by Chest-CAD are assigned to one of the following categories: Cardiac, Mediastinum/Hila, Lungs, Pleura, Bones, Soft Tissues, Hardware, or Other. Chest-CAD detects suspicious ROIs by analyzing radiographs using deep learning algorithms for computer vision and provides relevant annotations to assist physicians with their interpretations. For each image within a study, Chest-CAD generates a DICOM Presentation State file (output overlay). If any suspicious ROI is detected by Chest-CAD in the study, the output overlay for all images includes the text "ROI(s) Detected:" followed by a list of the category/categories for which suspicious ROI(s) were found, such as "Lungs, Bones". In addition, if suspicious ROI(s) are detected in the image, bounding boxes surrounding each detected suspicious ROI are included in the output overlay. If no suspicious ROI is detected by Chest-CAD in the study, the output overlay for each image will include the text "No ROI(s) Detected" and no bounding boxes will be included. Regardless of whether a suspicious ROI is detected, the overlay includes text identifying the X-ray study as analyzed by Chest-CAD and a customer configurable message containing a link to or instructions for users to access labeling. The Chest-CAD overlay can be toggled on or off by the physician within their Picture Archiving and Communication System (PACS) viewer, allowing for concurrent review of the X-ray study.

FractureDetect (FX) is a computer-assisted detection and diagnosis (CAD) software device to assist clinicians in detecting fractures during the review of radiographs of the musculoskeletal system. FX is indicated for adults only. FX is indicated for radiographs of the following industry-standard radiographic views and study types. | Study Type<br>(Anatomic Area<br>of Interest⁺) | Radiographic View(s)<br>Supported* | |-----------------------------------------------|------------------------------------| | Ankle | Frontal, Lateral, Oblique | | Clavicle | Frontal | | Elbow | Frontal, Lateral | | Femur | Frontal, Lateral | | Forearm | Frontal, Lateral | | Hip | Frontal, Frog Leg Lateral | | Humerus | Frontal, Lateral | | Knee | Frontal, Lateral | | Pelvis | Frontal | | Shoulder | Frontal, Lateral, Axillary | | Tibia / Fibula | Frontal, Lateral | | Wrist | Frontal, Lateral, Oblique | *For the purposes of this table, "Frontal" is considered inclusive of both posteroanterior (PA) and anteroposterior (AP) views. +Definitions of anatomic area of interest and radiographic views are consistent with the American College of Radiology (ACR) standards and guidelines.

FractureDetect (FX) is a computer-assisted detection and diagnosis (CAD) software device designed to assist clinicians in detecting fractures during the review of commonly acquired adult radiographs. FX does this by analyzing radiographs and providing relevant annotations, assisting clinicians in the detection of fractures within their diagnostic process at the point of care. FX was developed using robust scientific principles and industry-standard deep learning algorithms for computer vision. FX creates, as its output, a DICOM overlay with annotations indicating the presence or absence of fractures. If any fracture is detected by FX, the output overlay is composed to include the text annotation "Fracture: DETECTED" and to include one or more bounding boxes surrounding any fracture site(s). If no fracture is detected by FX, the output overlay is composed to include the text annotation "Fracture: NOT DETECTED" and no bounding box is included. Whether or not a fracture is detected, the overlay includes a text annotation identifying the radiograph as analyzed by FX and instructions for users to access labeling. The FX overlay can be toggled on or off by the clinicians within their PACS viewer, allowing for uninhibited concurrent review of the original radiograph.

OsteoDetect analyzes wrist radiographs using machine learning techniques to identify and highlight distal radius fractures during the review of posterior-anterior (PA) and lateral (LAT) radiographs of adult wrists.

OsteoDetect is a software device designed to assist clinicians in detecting distal radius fractures during the review of posterior-anterior (PA) and lateral (LAT) radiographs of adult wrists. The software uses deep learning techniques to analyze wrist radiographs (PA and LAT views) for distal radius fracture in adult patients.