Software Provides “Anatomic Intelligence” in Diagnostic Reading Applications
By MedImaging International staff writers Posted on 11 Dec 2013 |

Image: syngo.via General Engine is a new package of highly automated and standardized applications. As depicted here, the feature “Anatomical Range Presets” displays a quick, precise, optimal view of selected anatomical regions. (Photo courtesy of Siemens Healthcare).
A three-dimensional (3D) diagnostic reading solution features new applications and functionalities with software that “understands” human anatomy.
Siemens Healthcare’s (Erlangen, Germany) version VA30 of its routine 3D diagnostic reading software offers the syngo.via General Engine, a new package of highly automated and standardized applications. Anatomic 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 greater efficiency and enabling higher diagnostic effectiveness.
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, particularly in complicated diagnostic setting such as oncology.
Anatomic intelligence is also part of the new syngo.via General Engine software package with which customers can upgrade their software. The package includes the anatomic range presets feature, which displays a rapid, precise, optimal view of selected anatomic regions. To facilitate diagnoses, users often create such views manually, performing the multistep process of selecting the relevant area, aligning the image projections accordingly, and editing the detailed view. This takes time, requires anatomic expertise, and is error-prone. The new application from Siemens largely automates these steps, providing a consistent quality of the resulting anatomic views and images that does not depend on the skill of the specific user. Using a technology similar to facial recognition in digital photography, syngo.via is able to recognize spines, shoulders, and hips, in clinical images and optimize how they are displayed in their anatomical environment. The presets are initially available for specific anatomic regions in CT and MRI images.
The radiologic diagnostic report, following an examination, 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 these 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 relating 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 evaluation of the patient’s condition, which helps to improve the quality of treatment.
Syngo.via can be used as a standalone device or together with a range of syngo.via-based software options. The syngo.via General Engine is part of the medical device syngo.via. Rib labeling is not yet available in the United States.
Related Links:
Siemens Healthcare
Siemens Healthcare’s (Erlangen, Germany) version VA30 of its routine 3D diagnostic reading software offers the syngo.via General Engine, a new package of highly automated and standardized applications. Anatomic 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 greater efficiency and enabling higher diagnostic effectiveness.
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, particularly in complicated diagnostic setting such as oncology.
Anatomic intelligence is also part of the new syngo.via General Engine software package with which customers can upgrade their software. The package includes the anatomic range presets feature, which displays a rapid, precise, optimal view of selected anatomic regions. To facilitate diagnoses, users often create such views manually, performing the multistep process of selecting the relevant area, aligning the image projections accordingly, and editing the detailed view. This takes time, requires anatomic expertise, and is error-prone. The new application from Siemens largely automates these steps, providing a consistent quality of the resulting anatomic views and images that does not depend on the skill of the specific user. Using a technology similar to facial recognition in digital photography, syngo.via is able to recognize spines, shoulders, and hips, in clinical images and optimize how they are displayed in their anatomical environment. The presets are initially available for specific anatomic regions in CT and MRI images.
The radiologic diagnostic report, following an examination, 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 these 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 relating 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 evaluation of the patient’s condition, which helps to improve the quality of treatment.
Syngo.via can be used as a standalone device or together with a range of syngo.via-based software options. The syngo.via General Engine is part of the medical device syngo.via. Rib labeling is not yet available in the United States.
Related Links:
Siemens Healthcare
Latest Imaging IT News
- New Google Cloud Medical Imaging Suite Makes Imaging Healthcare Data More Accessible
- Global AI in Medical Diagnostics Market to Be Driven by Demand for Image Recognition in Radiology
- AI-Based Mammography Triage Software Helps Dramatically Improve Interpretation Process
- Artificial Intelligence (AI) Program Accurately Predicts Lung Cancer Risk from CT Images
- Image Management Platform Streamlines Treatment Plans
- AI-Based Technology for Ultrasound Image Analysis Receives FDA Approval
- AI Technology for Detecting Breast Cancer Receives CE Mark Approval
- Digital Pathology Software Improves Workflow Efficiency
- Patient-Centric Portal Facilitates Direct Imaging Access
- New Workstation Supports Customer-Driven Imaging Workflow
Channels
Radiography
view channel
AI Radiology Tool Identifies Life-Threatening Conditions in Milliseconds
Radiology is emerging as one of healthcare’s most pressing bottlenecks. By 2033, the U.S. could face a shortage of up to 42,000 radiologists, even as imaging volumes grow by 5% annually.... Read more
Machine Learning Algorithm Identifies Cardiovascular Risk from Routine Bone Density Scans
A new study published in the Journal of Bone and Mineral Research reveals that an automated machine learning program can predict the risk of cardiovascular events and falls or fractures by analyzing bone... Read more
AI Improves Early Detection of Interval Breast Cancers
Interval breast cancers, which occur between routine screenings, are easier to treat when detected earlier. Early detection can reduce the need for aggressive treatments and improve the chances of better outcomes.... Read more
World's Largest Class Single Crystal Diamond Radiation Detector Opens New Possibilities for Diagnostic Imaging
Diamonds possess ideal physical properties for radiation detection, such as exceptional thermal and chemical stability along with a quick response time. Made of carbon with an atomic number of six, diamonds... Read moreMRI
view channel
New MRI Technique Reveals Hidden Heart Issues
Traditional exercise stress tests conducted within an MRI machine require patients to lie flat, a position that artificially improves heart function by increasing stroke volume due to gravity-driven blood... Read more
Shorter MRI Exam Effectively Detects Cancer in Dense Breasts
Women with extremely dense breasts face a higher risk of missed breast cancer diagnoses, as dense glandular and fibrous tissue can obscure tumors on mammograms. While breast MRI is recommended for supplemental... Read moreUltrasound
view channel
New Incision-Free Technique Halts Growth of Debilitating Brain Lesions
Cerebral cavernous malformations (CCMs), also known as cavernomas, are abnormal clusters of blood vessels that can grow in the brain, spinal cord, or other parts of the body. While most cases remain asymptomatic,... Read more.jpeg)
AI-Powered Lung Ultrasound Outperforms Human Experts in Tuberculosis Diagnosis
Despite global declines in tuberculosis (TB) rates in previous years, the incidence of TB rose by 4.6% from 2020 to 2023. Early screening and rapid diagnosis are essential elements of the World Health... Read moreNuclear Medicine
view channel
New Imaging Approach Could Reduce Need for Biopsies to Monitor Prostate Cancer
Prostate cancer is the second leading cause of cancer-related death among men in the United States. However, the majority of older men diagnosed with prostate cancer have slow-growing, low-risk forms of... Read more
Novel Radiolabeled Antibody Improves Diagnosis and Treatment of Solid Tumors
Interleukin-13 receptor α-2 (IL13Rα2) is a cell surface receptor commonly found in solid tumors such as glioblastoma, melanoma, and breast cancer. It is minimally expressed in normal tissues, making it... Read moreGeneral/Advanced Imaging
view channel
CT Colonography Beats Stool DNA Testing for Colon Cancer Screening
As colorectal cancer remains the second leading cause of cancer-related deaths worldwide, early detection through screening is vital to reduce advanced-stage treatments and associated costs.... Read more
First-Of-Its-Kind Wearable Device Offers Revolutionary Alternative to CT Scans
Currently, patients with conditions such as heart failure, pneumonia, or respiratory distress often require multiple imaging procedures that are intermittent, disruptive, and involve high levels of radiation.... Read more
AI-Based CT Scan Analysis Predicts Early-Stage Kidney Damage Due to Cancer Treatments
Radioligand therapy, a form of targeted nuclear medicine, has recently gained attention for its potential in treating specific types of tumors. However, one of the potential side effects of this therapy... Read moreIndustry News
view channel
GE HealthCare and NVIDIA Collaboration to Reimagine Diagnostic Imaging
GE HealthCare (Chicago, IL, USA) has entered into a collaboration with NVIDIA (Santa Clara, CA, USA), expanding the existing relationship between the two companies to focus on pioneering innovation in... Read more
Patient-Specific 3D-Printed Phantoms Transform CT Imaging
New research has highlighted how anatomically precise, patient-specific 3D-printed phantoms are proving to be scalable, cost-effective, and efficient tools in the development of new CT scan algorithms... Read more
Siemens and Sectra Collaborate on Enhancing Radiology Workflows
Siemens Healthineers (Forchheim, Germany) and Sectra (Linköping, Sweden) have entered into a collaboration aimed at enhancing radiologists' diagnostic capabilities and, in turn, improving patient care... Read more