News | Artificial Intelligence | November 29, 2019

Oxipit to Showcase AI X-ray Longitudinal Comparison at RSNA

Dynamics enables a radiologist to compare X-rays and provide automatically generated reports specifically addressing the changes in images over the course of patient treatment

#RSNA19 Dynamics enables a radiologist to compare X-rays and provide automatically generated reports specifically addressing the changes in images over the course of patient treatment. Initially Dynamics feature will support longitudinal comparison for pneumothorax, consolidation, mass, nodule, pleural effusion, pulmonary edema and lung congestion radiological findings where progress reports are of greatest importance

November 29, 2019 — At RSNA19 Oxipit will offer a first public preview of Dynamics feature for its award winning ChestEye CAD suite. Dynamics enables a radiologist to compare X-rays and provide automatically generated reports specifically addressing the changes in images over the course of patient treatment. Initially Dynamics feature will support longitudinal comparison for pneumothorax, consolidation, mass, nodule, pleural effusion, pulmonary edema and lung congestion radiological findings where progress reports are of greatest importance. 

“In radiology a lot of X-ray reporting specifically deals with comparison of how a condition progresses over time. Operating ‘under-the-hood’, ChestEye automatically compares the latest radiograph with a previous chest X-ray of the same patient and produces a concise report, which includes a description of the observed changes. This feature enables further gains in radiologist productivity and improves the performance of other ChestEye suite components as well," noted CEO of Oxipit Gediminas Peksys.

For example, ChestEye may detect lung nodules in both the previous and the current image. With Dynamics, ChestEye compares the size of the nodules and describes the progress of the condition in an automatically generated report. In the words of Mr Peksys, this allows for more actionable treatment decisions and brings ChestEye reporting closer towards reports written by a radiologist.

The feature also improves the performance of ChestEye Queue — a triage solution for patient management - as it takes into account the progress of patient condition.

“Dynamics further builds upon the vanguard capabilities of Oxipit ChestEye deep learning models, which enables us to develop new solutions for a more efficient radiology workflow,” noted Peksys.

At the RSNA conference Oxipit will also present ChestEye Quality and ChestEye Negative solutions.

ChestEye Quality is an automated clinical audit service for retrospective X-ray report analysis. Working in the background, the product analyses chest X-ray images as well as accompanying reports. ChestEye Quality then automatically highlights cases with the highest likelihood of important discrepancies.

“Current quality assurance procedures only select a small random sample of reports for secondary specialist analysis. ChestEye Quality enables to double-check all retrospective patient cases. Contrary to a periodic clinical audit, The ChestEye Quality solution operates in real-time, enabling to identify discrepancies that may affect patient treatment,” said Peksys.

ChestEye Negative produces preliminary reports for chest X-ray images with no abnormality. This enables radiologists to focus on the images with pathology. The product significantly assists the radiologist, especially in clinical environments with a low fraction of abnormal studies, such as large scale health screening projects and out-patient clinics.

For more information: www.oxipit.ai

Related content:

Study: AI Found to Reduce Bias in Radiology Reports

Related Content

Table 1. Compared to 2-D mammography, which yields four images per patient, digital breast tomosynthesis (DBT), or 3-D mammography, produces hundreds of images per patient. While this provides more information for clinicians, the exponential increase in data can result in reader fatigue and burnout, which may ultimately affect patient care.

Table 1. Compared to 2-D mammography, which yields four images per patient, digital breast tomosynthesis (DBT), or 3-D mammography, produces hundreds of images per patient. While this provides more information for clinicians, the exponential increase in data can result in reader fatigue and burnout, which may ultimately affect patient care.

Sponsored Content | Case Study | Artificial Intelligence | April 09, 2020
As the largest independent imaging group in Michigan with 10 locations across the state,...
The interior of the German air force Airbus A-310 Medivac in Cologne, Germany, before its departure to Bergamo, Italy, March 28 to being ferrying COVID-19 patients to Germany for treatment to aid the Italians, whose healthcare system has been overwhelmed by the rapid spread of the coronavirus pandemic. Bundeswehr Photo by Kevin Schrief.

The interior of the German air force Airbus A-310 Medivac in Cologne, Germany, before its departure to Bergamo, Italy, March 28 to being ferrying COVID-19 patients to Germany for treatment to aid the Italians, whose healthcare system has been overwhelmed by the rapid spread of the coronavirus pandemic. Bundeswehr Photo by Kevin Schrief. Find more images from the COVID-19 pandemic.

 

Feature | Coronavirus (COVID-19) | April 08, 2020 | By Melinda Taschetta-Millane and Dave Fornell
In an effort to keep the imaging field updated on the latest information being released on coronavirus (COVID-19), th
#COVID19 #Coronavirus #2019nCoV #Wuhanvirus #SARScov2  The first of three clinical scenarios presented to the panel with final recommendations. Mild features refer to absence of significant pulmonary dysfunction or damage. Pre-test probability is based upon background prevalence of disease and may be further modified by individual’s exposure risk. The absence of resource constraints corresponds to sufficient availability of personnel, personal protective equipment, COVID-19 testing, hospital beds, and/or ve

 The first of three clinical scenarios presented to the panel with final recommendations. Mild features refer to absence of significant pulmonary dysfunction or damage. Pre-test probability is based upon background prevalence of disease and may be further modified by individual’s exposure risk. The absence of resource constraints corresponds to sufficient availability of personnel, personal protective equipment, COVID-19 testing, hospital beds, and/or ventilators with the need to rapidly triage patients. Contextual detail and considerations for imaging with CXR (chest radiography) versus CT (computed tomography) are presented in the text. (Pos=positive, Neg=negative, Mod=moderate). [Although not covered by this scenario and not shown in the figure, in the presence of significant resources constraints, there is no role for imaging of patients with mild features of COVID-19.] Image courtesy of the journal Radiology

News | Coronavirus (COVID-19) | April 07, 2020
April 7, 2020 — A multinational consens...
#COVID19 #Coronavirus #2019nCoV #Wuhanvirus #SARScov2 Chest CT findings of pediatric patients with COVID-19 on transaxial images. (a) Male, 2 months old, 2 days after symptom onset. Patchy ground-glass opacities GGO in the right lower lobe

Chest CT findings of pediatric patients with COVID-19 on transaxial images. Male, 2 months old, 2 days after symptom onset. Patchy ground-glass opacities GGO in the right lower lobe. Image courtesy of Radiology: Cardiothoracic Imaging

News | Coronavirus (COVID-19) | April 06, 2020
April 6, 2020 — Children and teenagers with COVID-19...
A recent study earlier this year in the journal Nature, which included researchers from Google Health London, demonstrated that artificial intelligence (AI) technology outperformed radiologists in diagnosing breast cancer on mammograms
Feature | Breast Imaging | April 06, 2020 | By Samir Parikh
A recent study earlier this year in the journal Nature,
Varian received FDA clearance for its Ethos therapy in February 2020. It is an adaptive intelligence solution that uses onboard AI in the treatment system to take the cone beam CT imaging on the system, compare it to the treatment plan and deliver an entire adaptive treatment plan in a typical 15-minute treatment time slot, from patient setup through treatment delivery.

Varian received FDA clearance for its Ethos therapy in February 2020, shown here displayed for the first time at ASTRO 2019. It is an adaptive intelligence solution that uses onboard AI in the treatment system to take the cone beam CT imaging on the system, compare it to the treatment plan and deliver an entire adaptive treatment plan in a typical 15-minute treatment time slot, from patient setup through treatment delivery.

Feature | Treatment Planning | April 03, 2020 | Dave Fornell, Editor
The traditional treatment planning process takes days to create an optimized radiation therapy delivery plan, but new
An example of Philips’ TrueVue technology, which offers photo-realistic rendering and the ability to change the location of the lighting source on 3-D ultrasound images. In this example of two Amplazer transcatheter septal occluder devices in the heart, the operator demonstrating the product was able to push the lighting source behind the devices into the other chamber of the heart. This illuminated a hole that was still present that the occluders did not seal.

An example of Philips’ TrueVue technology, which offers photo-realistic rendering and the ability to change the location of the lighting source on 3-D ultrasound images. In this example of two Amplazer transcatheter septal occluder devices in the heart, the operator demonstrating the product was able to push the lighting source behind the devices into the other chamber of the heart. This illuminated a hole that was still present that the occluders did not seal. Photo by Dave Fornell

Feature | Radiology Imaging | April 02, 2020 | By Katie Caron
A new year — and decade — offers the opportunity to reflect on the advancements and challenges of years gone by and p
#COVID19 #Coronavirus #2019nCoV #Wuhanvirus

Getty Images

Feature | Coronavirus (COVID-19) | April 02, 2020 | Jilan Liu and HIMSS Greater China Team
Information technologies have played a pivotal role in China’s response to the novel coronavirus...