InferRead Lung CT.AI is designed to support concurrent reading and is designed to aid radiologists in pulmonary nodule detection during the review of chest computed tomography (CT) scans, increasing accuracy and efficiency.

August 4, 2020 — Infervision received U.S. Food and Drug Administration (FDA) 510(K) clearance of the InferRead Lung CT.AI product, which uses the state-of-the-art artificial intelligence and deep learning technology, to automatically perform lung segmentation, along with accurately identifying and labeling nodules of different types. InferRead Lung CT.AI is designed to support concurrent reading and is designed to aid radiologists in pulmonary nodule detection during the review of chest computed tomography (CT) scans, increasing accuracy and efficiency.

With five years of international clinical use, Infervision’s InferRead Lung CT.AI application is a robust and powerful tool to serve the radiologist.

InferRead Lung CT.AI is currently in use at over 380 hospitals and imaging centers globally. More than 55,000 cases daily are being processed by the system, and over 19 million patients have already benefited from this advanced AI technology. “Fast, workflow friendly, and accurate are the three key areas we have emphasized during product development. We’re excited to be able to make our InferRead Lung CT.AI solution available to the North American market. Our clients tell us it has great potential to help provide improved outcomes for providers and patients alike,” said Matt Deng, Ph.D., director of Infervision North America. The Company offers the system under a number of pricing options to meet everyone’s needs.

The company also predicts the system may also be of great benefit to lung cancer screening (LCS) programs across the nation. Lung cancer is the second most common cancer in both men and women in the U.S. It might have around a 60% 5-year survival rate if discovered at the early stage. However, the survival rate is lower than 10% if progressed to the later stages without timely follow-up and treatment.

The Lung Cancer Screening program has been designed to encourage the early diagnosis and treatment of the high-risk population meeting certain criteria. The screening process involves low-dose CT (LDCT) scans to determine any presence of lung nodules or early-stage lung disease. However small nodules can be very difficult to detect. Missed diagnoses are not uncommon. “The tremendous potential for lung cancer screening to reduce mortality in the U.S. is very much unrealized due to a combination of reasons.  Based on our experience reviewing the algorithm for the past several months and my observations of its extensive use and testing in China, I believe that Infervision’s InferRead Lung CT.AI application can serve as a robust lung nodule “spell-checker” with the potential to improve diagnostic accuracy, reduce reading times, and integrate with the image review workflow,” said Eliot Siegel, M.D., professor and vice chair of research information systems in radiology at the University of Maryland School of Medicine.

InferRead Lung CT.AI is now FDA cleared, and has also received the CE mark in Europe. “This is our first FDA clearance for the deep-learning-based chest CT algorithm and it will lead the way to better integration of advanced A.I. solutions to help the healthcare clinical workflow in the region,” according to Deng, “This marks a great start in the North American market, and we are expecting more high-performance AI tools in the near future.”

For more information: us.infervision.com

 


Related Content

News | Radiology Business

February 2, 2023 — Five additional imaging centers across Allegheny Health Network (AHN) have been recognized by the ...

Time February 02, 2023
arrow
Feature | Radiology Business | By Melinda Taschetta-Millane

Here is a recap of what ITN viewers found most interesting during the month of January: 1. A Look at the Changes in 2023 ...

Time February 01, 2023
arrow
News | PET Imaging

January 31, 2023 — Electronic cigarette (e-cigarette) users have greater lung inflammation than cigarette smokers and ...

Time January 31, 2023
arrow
News | Ultrasound Imaging

January 31, 2023 — Esaote, a leading Italian company in the biomedical sector – in ultrasound, dedicated MRI and medical ...

Time January 31, 2023
arrow
Webinar | Information Technology

Postpandemic staffing shortages and increased volumes require radiologists to do more with less, exacerbating burnout ...

Time January 30, 2023
arrow
News | Digital Pathology

January 27, 2023 — Fujifilm has completed its asset purchase of Inspirata, Inc.’s digital pathology business effective ...

Time January 27, 2023
arrow
News | Artificial Intelligence

January 26, 2023 — MedCognetics, Inc., an Artificial Intelligence (AI) software firm, announced that it has been awarded ...

Time January 26, 2023
arrow
News | Artificial Intelligence

Artificial intelligence (AI) is playing a growing role in all our lives and has shown promise in addressing some of the ...

Time January 26, 2023
arrow
News | Digital Pathology

January 25, 2023 — mTuitive, Inc. and PathPresenter Corporation announced a new partnership to deliver an enhanced ...

Time January 25, 2023
arrow
News | Magnetic Resonance Imaging (MRI)

January 25, 2023 — On November 11th, 2022 at the Southern Hills Hospital in Las Vegas, USA, Robotic Spine Surgeon Dr ...

Time January 25, 2023
arrow
Subscribe Now