CAD Software for Digital Mammography Employs Algorithmic Voting for Better Performance
By MedImaging International staff writers Posted on 30 Nov 2011 |
A next-generation computer-aided detection (CAD) software was developed to help radiologists improve breast cancer detection. The system makes significant performance improvements over its predecessor and additionally reduces the possibility for false-positive rates when detecting suspicious lesions on mammograms.
Parascript, LLC (Longmont, CO, USA), an image analysis and pattern recognition technology provider, announced the release of AccuDetect 5.0, which is designed to work with the leading full field digital mammography (FFDM) and computed radiography (CR) systems. The software received CE marking approval and is installed in multiple radiology centers in France, Italy, and The Netherlands. It is also used by the Russian Center for Roentgeno-Radiology Research (RNCRR; Moscow, Russia), Russia’s largest, most recognized breast cancer oncology center.
Available for FFDM vendors interested in reducing false-positive rates of existing CAD systems, AccuDetect is intended to help radiologists in the early detection of breast cancer during mammography screening exams. The technology has been developed using a large database of digital images from leading digital mammography systems. It uses several proprietary complementary algorithms to identify the presence of suspicious lesions on mammogram images. Proprietary voting technology combines the detection results from each algorithm. The result is an innovative CAD product with high sensitivity and low false-positive rates.
“We are proud to leverage our expertise in image analysis and pattern recognition to help radiologists detect suspicious lesions on mammograms. We are especially excited, at Parascript, to report the significant strides and multiple deployments we have accomplished this year with AccuDetect 5.0,” said Yuri Prizemin, director of business development for medical imaging for Parascript.
CAD systems are typically utilized to identify and highlight hard-to-find anomalies on medical images. The technology enables suspicious lesions to be brought to the attention of radiologists. AccuDetect automatically identifies and distinctly marks suspicious areas, enabling a more accurate interpretation of mammograms and increased detection of calcifications and masses.
The Parascript image analysis suite extracts important data from images. Employing patented digital image analysis and pattern recognition technologies, the Parascript image analysis suite improves decision quality in medical imaging, postal and payment automation, fraud detection, and forms processing operations. Parascript software processes over 100 billion imaged documents per year.
Related Links:
Parascript
Parascript, LLC (Longmont, CO, USA), an image analysis and pattern recognition technology provider, announced the release of AccuDetect 5.0, which is designed to work with the leading full field digital mammography (FFDM) and computed radiography (CR) systems. The software received CE marking approval and is installed in multiple radiology centers in France, Italy, and The Netherlands. It is also used by the Russian Center for Roentgeno-Radiology Research (RNCRR; Moscow, Russia), Russia’s largest, most recognized breast cancer oncology center.
Available for FFDM vendors interested in reducing false-positive rates of existing CAD systems, AccuDetect is intended to help radiologists in the early detection of breast cancer during mammography screening exams. The technology has been developed using a large database of digital images from leading digital mammography systems. It uses several proprietary complementary algorithms to identify the presence of suspicious lesions on mammogram images. Proprietary voting technology combines the detection results from each algorithm. The result is an innovative CAD product with high sensitivity and low false-positive rates.
“We are proud to leverage our expertise in image analysis and pattern recognition to help radiologists detect suspicious lesions on mammograms. We are especially excited, at Parascript, to report the significant strides and multiple deployments we have accomplished this year with AccuDetect 5.0,” said Yuri Prizemin, director of business development for medical imaging for Parascript.
CAD systems are typically utilized to identify and highlight hard-to-find anomalies on medical images. The technology enables suspicious lesions to be brought to the attention of radiologists. AccuDetect automatically identifies and distinctly marks suspicious areas, enabling a more accurate interpretation of mammograms and increased detection of calcifications and masses.
The Parascript image analysis suite extracts important data from images. Employing patented digital image analysis and pattern recognition technologies, the Parascript image analysis suite improves decision quality in medical imaging, postal and payment automation, fraud detection, and forms processing operations. Parascript software processes over 100 billion imaged documents per year.
Related Links:
Parascript
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
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 more
AI-Powered Imaging Technique Shows Promise in Evaluating Patients for PCI
Percutaneous coronary intervention (PCI), also known as coronary angioplasty, is a minimally invasive procedure where small metal tubes called stents are inserted into partially blocked coronary arteries... Read moreMRI
view channel
AI Tool Predicts Relapse of Pediatric Brain Cancer from Brain MRI Scans
Many pediatric gliomas are treatable with surgery alone, but relapses can be catastrophic. Predicting which patients are at risk for recurrence remains challenging, leading to frequent follow-ups with... Read more
AI Tool Tracks Effectiveness of Multiple Sclerosis Treatments Using Brain MRI Scans
Multiple sclerosis (MS) is a condition in which the immune system attacks the brain and spinal cord, leading to impairments in movement, sensation, and cognition. Magnetic Resonance Imaging (MRI) markers... Read more
Ultra-Powerful MRI Scans Enable Life-Changing Surgery in Treatment-Resistant Epileptic Patients
Approximately 360,000 individuals in the UK suffer from focal epilepsy, a condition in which seizures spread from one part of the brain. Around a third of these patients experience persistent seizures... Read moreUltrasound
view channel.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 more
AI Identifies Heart Valve Disease from Common Imaging Test
Tricuspid regurgitation is a condition where the heart's tricuspid valve does not close completely during contraction, leading to backward blood flow, which can result in heart failure. A new artificial... Read moreNuclear Medicine
view channel
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 more
Novel PET Imaging Approach Offers Never-Before-Seen View of Neuroinflammation
COX-2, an enzyme that plays a key role in brain inflammation, can be significantly upregulated by inflammatory stimuli and neuroexcitation. Researchers suggest that COX-2 density in the brain could serve... Read moreGeneral/Advanced Imaging
view channel
AI-Powered Imaging System Improves Lung Cancer Diagnosis
Given the need to detect lung cancer at earlier stages, there is an increasing need for a definitive diagnostic pathway for patients with suspicious pulmonary nodules. However, obtaining tissue samples... Read more
AI Model Significantly Enhances Low-Dose CT Capabilities
Lung cancer remains one of the most challenging diseases, making early diagnosis vital for effective treatment. Fortunately, advancements in artificial intelligence (AI) are revolutionizing lung cancer... 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