News | Ultrasound Imaging | December 09, 2019

DiA Joins with IBM Watson Health to Arm Clinicians with its AI-powered Cardiac Ultrasound Software

DiA’s novel solution leverages AI to transform the way clinicians capture and analyze ultrasound images. By adding DiA to its AI Marketplace, IBM Watson Health will offer clinicians access to objective and accurate ultrasound analysis

DiA’s novel solution leverages AI to transform the way clinicians capture and analyze ultrasound images

December 9, 2019 —  DiA Imaging Analysis Ltd., an IBM Alpha Zone Accelerator Alumni Startup, announces a collaboration with IBM Watson Health, a leading provider of innovative AI, enterprise imaging, and interoperability solutions used by medical professionals worldwide. The IBM Imaging AI Marketplace will offer DiA’s FDA-cleared, AI-powered cardiac ultrasound software, designed to assist clinicians to analyze cardiac ultrasound images automatically.

Analyzing ultrasound images is often a visual process that can be challenging and highly dependent on user experience. DiA’s solutions address this challenge by assisting clinicians to objectively and accurately analyze ultrasound images, reducing the subjectivity associated with visual interpretation.

With the launch of the IBM Imaging AI Marketplace, IBM will be introducing DiA’s LVivo EF solution, one of several cardiology and general imaging AI solutions that the company has developed.  DiA’s LVivo EF application offers clinicians an AI-based quantification solution that will provide automated clinical data such as Ejection Fraction (EF) and Global Longitudinal Strain (GLS). The company anticipates adding additional solutions to the Marketplace in the near future.  

“IBM Watson Health is proud to announce a collaboration with DiA Imaging,” said Anne Le Grand, General Manager, Imaging, Life Sciences and Oncology, IBM Watson Health. “DiA’s innovative AI-powered offerings can provide our clients with the ability to analyze images with advanced AI-based solutions which can support IBM Watson Health’s mission to help build smarter health ecosystems.”

“Our collaboration with IBM Watson Health demonstrates the implementation of DiA’s vision to make the analysis of ultrasound images smarter and accessible to clinicians with various levels of experience, on any platform,” said Hila Goldman-Aslan, CEO and Co- Founder of DiA Imaging Analysis. “We are proud to offer our cross-platform, vendor-neutral solutions to healthcare providers in the IBM Watson Health’s ecosystem, leading the change to help transform ultrasound analysis with AI.”

DiA demonstrated its full suite of LVivo and additional solutions during the Radiological Society of North America’s (RSNA) 2019 annual meeting in Chicago. DiA’s AI was highlighted and demonstrated at the IBM Watson Health Booth.

For more information: www.dia-analysis.com

Related Content

#COVID19 #Coronavirus #2019nCoV #Wuhanvirus #SARScov2

Typical CT imaging features for COVID-19. Unenhanced, thin-section axial images of the lungs in a 52-year-old man with a positive RT-PCR (A-D) show bilateral, multifocal rounded (asterisks) and peripheral GGO (arrows) with superimposed interlobular septal thickening and visible intralobular lines (“crazy-paving”). Routine screening CT for diagnosis or exclusion of COVID-19 is currently not recommended by most professional organizations or the US Centers for Disease Control and Prevention. Image courtesy of RSNA

News | Coronavirus (COVID-19) | March 26, 2020
March 26, 2020 — The Radiological Society of North America (RSNA
#COVID19 #Coronavirus #2019nCoV #Wuhanvirus #SARScov2

Representative examples of the attention heatmaps generated using Grad-CAM method for (a) COVID-19, (b) CAP, and (c) Non-Pneumonia. The heatmaps are standard Jet colormap and overlapped on the original image, the red color highlights the activation region associated with the predicted class. COVID-19 = coronavirus disease 2019, CAP = community acquired pneumonia. Image courtesy of the journal Radiology

News | Coronavirus (COVID-19) | March 20, 2020
March 20, 2020 — An arti...
#COVID19 #Coronavirus #2019nCoV #Wuhanvirus #SARScov2

Series CT scans in 35-year-old woman with COVID-19 pneumonia. (a) Scan obtained on illness days 1 showed multiple pure ground-glass opacity (GGO) mainly in right lower lobe. (b) Scan obtained on illness days 5 showed increased extent of GGO and early consolidation. (c) Scan obtained on illness days 11 showed multiple consolidation with almost the same extent. (d) Scan obtained on illness days 15 showed a mixed pattern with a slightly smaller extent, and the perilobular consolidation might suggest the presence of organizing pneumonia. The patient was discharged on illness days 17. Image courtesy of the journal Radiology

News | Coronavirus (COVID-19) | March 20, 2020
March 20, 2020 — In a new study pub
#COVID19 #Coronavirus #2019nCoV #Wuhanvirus #SBI20

Image courtesy of Getty Images

News | Coronavirus (COVID-19) | March 17, 2020
March 17, 2020 — The journal Radiology ...
Two examples of CT myocardial perfusion (CTP) imaging assessment software. Canon is on the left and GE Healthcare is on the right. Both of these technologies have been around for a few years, but there have been an increasing amount of clinical data from studies showing the accuracy of the technology compared to nuclear imaging, the current stand of care for myocardial perfusion imaging, and cardiac MRI. #SCCT #perfusionimaging 

Two examples of CT myocardial perfusion (CTP) imaging assessment software. Canon is on the left and GE Healthcare is on the right. Both of these technologies have been around for a few years, but there have been an increasing amount of clinical data from studies showing the accuracy of the technology compared to nuclear imaging, the current stand of care for myocardial perfusion imaging, and cardiac MRI.

News | Computed Tomography (CT) | March 16, 2020
March 16, 2020 — The Society of Cardiovascular Computed Tomography (SCCT) released a new...
The low-dose chest computed tomography (CT) scans used in lung cancer screening do not appear to damage human DNA

Immunofluorescent staining performed to depict γ-H2AX foci. Representative images of γ-H2AX foci in peripheral blood lymphocytes in an 82-year-old woman who underwent standard-dose CT. (a) Nuclear DNA of four lymphocytes. (b) γ-H2AX foci (arrows). (c) Markers of DNA double-strand breaks. In this merged image, DNA is blue and γ-H2AX foci are red (arrows show small foci). γ-H2AX, a marker of DNA double-strand breaks, is a phosphorylated type of histone H2AX. Scale bar: 5 mm. Image courtesy of the Radiological Society of North America

News | Lung Cancer | March 11, 2020
March 11, 2020 — The low-dose chest computed tomog...
DBT, sometimes called 3-D mammography, emerged in the last decade as a powerful tool for breast cancer screening

Images in a 57-year-old woman noted to have "good prognosis" invasive cancer detected at digital breast tomosynthesis (DBT) screening. (a) Craniocaudal view of the left breast obtained with the two-dimensional digital mammography (DM) portion of the DM/DBT screening study demonstrates a subtle area of distortion in the medial left breast. (b) Single-slice image from the left craniocaudal DBT portion of the screening study shows an area of bridging distortion (circle). (c) Electronically enlarged image of the area of concern seen on the left craniocaudal view in a single DBT slice as shown in b. (d) Targeted US scan demonstrates two small adjacent irregular solid masses. US-guided core biopsy yielded an invasive carcinoma of the tubular subtype that was estrogen receptor positive, progesterone receptor positive, and human epidermal growth factor receptor 2 negative. The results of the sentinel node biopsy were negative. Image courtesy of the Radiological Society of North America

News | Breast Imaging | March 11, 2020
March 11, 2020 — A new study published in the journal ...
Schematic depiction of the automated process for assessing fat, muscle, liver, aortic calcification, and bone from original abdominal CT scan data

Figure 1: Depiction of the fully automated CT biomarkers tools used in this study. (A) Schematic depiction of the automated process for assessing fat, muscle, liver, aortic calcification, and bone from original abdominal CT scan data. (B) Case example in an asymptomatic 52-year-old man undergoing CT for colorectal cancer screening. At the time of CT screening, he had a body-mass index of 27·3 and Framingham risk score of 5% (low risk). However, several CT-based metabolic markers were indicative of underlying disease. Multivariate Cox model prediction based on these three CT-based results put the risk of cardiovascular event at 19% within 2 years, at 40% within 5 years, and at 67% within 10 years, and the risk of death at 4% within 2 years, 11% within 5 years, and 27% within 10 years. At longitudinal clinical follow-up, the patient suffered an acute myocardial infarction 3 years after this initial CT and died 12 years after CT at the age of 64 years. (C) Contrast-enhanced CT performed 7 months before death for minor trauma was interpreted as negative but does show significant progression of vascular calcification, visceral fat, and hepatic steatosis. HU=Hounsfield units.

News | Computed Tomography (CT) | March 06, 2020
March 6, 2020 — Researchers at the National Institutes of Health a