Fovia Ai rolls out AI software at RSNA 2019

AuntMinnie.com staff writers
Dec 1, 2019
2019 12 02 19 42 3533 Fovia Ai X Stream Ai Cockpit 20191202194647

Fovia Ai, a subsidiary of advanced visualization firm Fovia, released its artificial intelligence (AI) software XStream aiCockpit and XStream aiPlatform at RSNA 2019 in Chicago.

The XStream aiCockpit and XStream aiPlatform. Image courtesy of Fovia Ai.The XStream aiCockpit and XStream aiPlatform. Image courtesy of Fovia Ai.

XStream aiCockpit provides radiologists access to AI-driven workflows and visualizations that are readily launched from any PACS, worklist, dictation software, or hospital system. XStream aiCockpit is 2D and 3D visualization software, accessible as a white‑label product or through native integration.

XStream aiPlatform is a vendor-neutral software that connects AI developers, PACS, and hospital systems. The PACS maintains control over the AI workflow by selecting which algorithms should be made available, controlling AI results and, thus, allowing such results to be viewed by XStream aiCockpit or inside a different PACS viewer.

Latest in Artificial Intelligence
Bmd
16 Bit gets FDA nod for AI x-ray software
April 12, 2024
Predictions and Grad-CAMs of ViT-based models on sample PET/CT, PET, and CT test images from the “positive” class. ViT was fine-tuned using training data for each modality. The bounding boxes depicted in the figure indicate malignant lesions. The top row of the Grad-CAMs shows important areas for “positive” predictions, and the bottom row shows areas for “negative” predictions. Image courtesy of Scientific Reports.
Vision transformer AI model boosts PET/CT imaging of cancer
April 12, 2024
Jennifer Bagley from the University of Oklahoma presents findings at UltraCon on the performance of two machine learning approaches in predicting burnout among sonographers.
UltraCon: Machine learning predicts sonographer burnout
April 9, 2024
Breast Cancer 3 D
AI helps select patients for supplemental breast cancer screening
April 9, 2024
Related Stories
2019 12 02 19 42 3533 Fovia Ai X Stream Ai Cockpit 20191202194637
Artificial Intelligence
Fovia Ai introduces AI products at RSNA 2020
2019 06 27 17 42 3952 Business Man Handshake 400
Artificial Intelligence
Fovia Ai, Nvidia partner on AI
2016 09 02 09 36 05 93 Fda Logo V2 400
Artificial Intelligence
FDA to host workshop on artificial intelligence
2019 11 15 21 20 3865 Rsna Technical Exhibits 400
Artificial Intelligence
Care Mentor AI presents latest AI diagnostics at RSNA
More in Artificial Intelligence
16 Bit gets FDA nod for AI x-ray software
By AuntMinnie.com staff writers
Canadian AI software developer 16 Bit has received de novo approval from the U.S. Food and Drug Administration (FDA) for Rho, an AI tool for evaluating low bone mineral density.
April 12, 2024
Bmd
Vision transformer AI model boosts PET/CT imaging of cancer
By Will Morton
A vision transformer AI model outperformed convolutional neural networks when classifying tumors on PET/CT images as benign or malignant.
April 12, 2024
Predictions and Grad-CAMs of ViT-based models on sample PET/CT, PET, and CT test images from the “positive” class. ViT was fine-tuned using training data for each modality. The bounding boxes depicted in the figure indicate malignant lesions. The top row of the Grad-CAMs shows important areas for “positive” predictions, and the bottom row shows areas for “negative” predictions. Image courtesy of Scientific Reports.
UltraCon: Machine learning predicts sonographer burnout
By Amerigo Allegretto
Machine-learning approaches can predict burnout among sonographers, though established burnout indices may be enough, according to research presented April 9 at UltraCon.
April 9, 2024
Jennifer Bagley from the University of Oklahoma presents findings at UltraCon on the performance of two machine learning approaches in predicting burnout among sonographers.
AI helps select patients for supplemental breast cancer screening
By Erik L. Ridley
An AI-based method can outperform breast density measurements for flagging patients who would benefit from supplemental breast cancer screening.
April 9, 2024
Breast Cancer 3 D
AI model predicts invasiveness of lung cancer on CT scans
By Will Morton
Radiologists in Beijing, China, have developed a joint deep-learning and radiomics AI model that can flag how invasive tumors may be in patients with lung cancer.
April 9, 2024
Lung Ai
Can AI improve sustainability in nuclear medicine?
Nuclear medicine experts support the use of AI to improve sustainability of practices in the field, yet say implementation will require careful consideration of the technology’s benefits and detriments.
April 9, 2024
ChatGPT powered by GPT-4 and using DALL-E−3 was asked to generate an image for teaching purposes that demonstrated: a nuclear medicine bone scan with skeletal metastases (top left); coronary artery disease (top right); an F-18 FDG-PET scan of the brain with Alzheimer's disease (bottom left); and an x-ray showing a fracture (bottom right). These are misleading for educational purposes and for patients who may be searching for information. Image and caption courtesy of Radiography.
Northwestern, Dell develop LLM for chest x-ray interpretation
By AuntMinnie.com staff writers
Dell Technologies and Northwestern Medicine are collaborating on a generative multimodal large language model (LLM) for the interpretation of chest x-rays.
April 5, 2024
Chest Lung Xray 400
SPECT/CT algorithm predicts heart failure hospitalizations
By Will Morton
AI can effectively predict hospitalization for acute heart failure exacerbation in patients undergoing SPECT/CT myocardial perfusion imaging.
April 3, 2024
A visual abstract of the study by the authors. Image courtesy of the Journal of Nuclear Medicine.
ChatGPT performs well on radiation oncology patient care questions
By Will Morton
ChatGPT may be a valuable resource for radiation oncology patients.
April 2, 2024
Chatgpt1
Can AI help chest DDR achieve clinical adoption?
By Will Morton
Chest dynamic digital radiography (DDR) may have received a boost toward clinical use in patients with lung disorders, with researchers developing AI to perform time-consuming analysis involved in the technology.
April 1, 2024
(a) Raw example of a dynamic digital radiograph. (b) Contrast equalization using contrast-limited adaptive equalization shows improved anatomical visualization. (c) Training data is generated through manually labeling using SLEAP’s graphical user interface. (d-e) Neural network detection schematic. For each quadrant a series of two networks were used. The first identifies the quadrant center, the second using input of the first, then identifies individual anatomical landmarks within a quadrant. (d) Four neural networks were trained, each with the objective of identifying a chest quadrant centroid. The four separate quadrants are visualized as colored boxes (right upper quadrant, green; right lower quadrant, blue; left upper quadrant, red; left lower quadrant, yellow). (e) Serial centroid then anatomical identification. Two quadrant examples showing confidence maps of trained neural networks identifying quadrant centroids (left) and then anatomical confidence maps (right). Image and caption courtesy of Chest Pulmonary.
Deep learning helps distinguish benign vertebral fractures on CT
By Kate Madden Yee
A deep-learning algorithm used with CT imaging can differentiate between benign and malignant vertebral fractures, researchers have found.
March 27, 2024
Overview of the automated deep learning-based pipeline. Multidetector CT images show the (A) original data, (B, C) vertebral segmentation, and (D-F) vertebral labeling during preprocessing. Images and caption courtesy of the RSNA.
Large language models simplify radiology report impressions
By Erik L. Ridley
Large language models can significantly simplify radiology report impressions, enhancing readability for patients, according to recently published research.
March 26, 2024
Chat Gpt Artificial Intelligence Ai Head
Page 1 of 365
Next Page