New Version of syngo.via brings "Anatomical Intelligence" to Diagnostic Reading

Siemens HealthcareSiemens Healthcare introduces version VA30 of its routine 3D and advanced reading software syngo.via, featuring new applications and functionalities that further streamline and accelerate the syngo.via experience. The latest innovation is the syngo.via General Engine, a new package of highly automated and standardized applications. "Anatomical Range Presets," for example, identifies individual regions of the body on images captured using computed tomography (CT) and magnetic resonance imaging (MRI), aligns the image projections accordingly, then selects detailed views to facilitate case preparation. For customers, this means greater efficiency and enables higher diagnostic confidence.

Siemens is making syngo.via more anatomically intelligent to support radiologists and medical technology personnel in their routine workflows. The software "understands" human anatomy and prepares the images for diagnostic reading. Syngo.via VA30 features "Automatic Rib Labeling," for example, which automatically identifies and labels the ribs in CT scans. Until now, radiologists had to identify the ribs manually. Given the unique shape of the ribs, this can be time-consuming and lead to errors, especially in complex diagnostic environments such as oncology.

Anatomical intelligence is also a hallmark of the new syngo.via General Engine software package with which customers can upgrade their software. The package includes the "Anatomical Range Presets" feature, which displays a quick, precise, optimal view of selected anatomical regions. To facilitate diagnoses, users often create such views manually, performing the multi-step process of selecting the relevant area, aligning the image projections accordingly, and editing the detailed view. This takes time, requires anatomical expertise, and is error-prone. The new application from Siemens largely automates these steps. This delivers a consistent quality of the resulting anatomical views and snapshots that does not depend on the skill of the specific user. Using a technology akin to facial recognition in digital photography, syngo.via is able to recognize shoulders, spines, hips, etc. in clinical images and optimize how they are displayed in their anatomical environment. The presets are initially available for specific anatomical regions in CT and MRI images.

Following an examination, the radiological diagnostic report plays a key role in the treatment of the patient. The syngo.via Advanced Reporting tool, part of the syngo.via General Engine, helps radiologists create clear, well-structured reports for the referring or follow-up physicians. Standardized templates make it easier to create reports but can still be customized to individual needs, and findings from multiple examinations can be consolidated into a single report. In the past, multiple diagnoses meant having different documents pertaining to a single case. Now, the diagnostic report reflects the patient's entire disease profile. This makes it much easier for doctors to form a comprehensive assessment of the patient's condition, which helps to improve the quality of treatment.

Related news articles:

About Siemens Healthcare
The Siemens Healthcare Sector is one of the world's largest suppliers to the healthcare industry and a trendsetter in medical imaging, laboratory diagnostics, medical information technology and hearing aids. Siemens offers its customers products and solutions for the entire range of patient care from a single source - from prevention and early detection to diagnosis, and on to treatment and aftercare. By optimizing clinical workflows for the most common diseases, Siemens also makes healthcare faster, better and more cost-effective. Siemens Healthcare employs some 52,000 employees worldwide and operates around the world. In fiscal year 2013 (to September 30), the Sector posted revenue of 13.6 billion euros and profit of 2.0 billion euros.

Most Popular Now

Do Fitness Apps do More Harm than Good?

A study published in the British Journal of Health Psychology reveals the negative behavioral and psychological consequences of commercial fitness apps reported by users on social media. These impacts may...

AI Tool Beats Humans at Detecting Parasi…

Scientists at ARUP Laboratories have developed an artificial intelligence (AI) tool that detects intestinal parasites in stool samples more quickly and accurately than traditional methods, potentially transforming how labs diagnose...

Making Cancer Vaccines More Personal

In a new study, University of Arizona researchers created a model for cutaneous squamous cell carcinoma, a type of skin cancer, and identified two mutated tumor proteins, or neoantigens, that...

AI, Health, and Health Care Today and To…

Artificial intelligence (AI) carries promise and uncertainty for clinicians, patients, and health systems. This JAMA Summit Report presents expert perspectives on the opportunities, risks, and challenges of AI in health...

AI can Better Predict Future Risk for He…

A landmark study led by University' experts has shown that artificial intelligence can better predict how doctors should treat patients following a heart attack. The study, conducted by an international...

A New AI Model Improves the Prediction o…

Breast cancer is the most commonly diagnosed form of cancer in the world among women, with more than 2.3 million cases a year, and continues to be one of the...

AI System Finds Crucial Clues for Diagno…

Doctors often must make critical decisions in minutes, relying on incomplete information. While electronic health records contain vast amounts of patient data, much of it remains difficult to interpret quickly...

New AI Tool Makes Medical Imaging Proces…

When doctors analyze a medical scan of an organ or area in the body, each part of the image has to be assigned an anatomical label. If the brain is...