We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

Features Partner Sites Information LinkXpress hp
Sign In
Advertise with Us
GLOBETECH PUBLISHING LLC

Download Mobile App




Fully Automated CAD Application Successful in Onsite Liver Tumor Segmentation Competition

By MedImaging International staff writers
Posted on 01 Oct 2008
Print article
In a recent medical imaging competition, a fully automated liver segmentation application was able to correctly and consistently identify and segment 30 liver lesions representing a range of patients and pathologies.

Definiens (Munich, Germany) placed first in the 2008 Liver Tumor Segmentation Grand Challenge's live contest, organized by the International Society of Medical Image Computing and Computer-Assisted Interventions (MICCAI), held at New York University (New York, NY, USA) in September 2008.

Against a field of the world's leading research groups in the area of liver lesion segmentation, Definiens' fully automated computer-aided detection (CAD) application outperformed all other methods, including the interactive ones, and received the live competition's highest scores.

Definiens' applications accurately and consistently identified and segmented liver lesions in a series of computed tomography (CT) images from various patients. Overall, the Grand Challenge compared the brain lesion, coronary tracking, and liver-lesion segmentation techniques of 36 industry and academic teams. The performance of the liver-lesion segmentation techniques was evaluated using a set of comprehensive measures, including tumor surface area and volume.

Definiens' automatic analysis was compared against manual segmentations performed by several experienced radiologists. The success of the Definiens team in the competition followed an impressive third placing in the fully automated category of the MICCAI Segmentation of the Liver Competition 2007 (SLIVER07). Successive victories in the challenging MICCAI contests provide further validation for Definiens' pioneering semi- and fully-automated CAD applications.

"It is always a boost to receive clinical and scientific recognition for our exciting work in automated image analysis and our strong finish speaks to the innovation behind Definiens' technology,” said Frank P. Klein, VP of Medical Imaging at Definiens. "We are currently developing CAD applications for a variety of challenging cancer targets, including lung, liver, and lymph nodes.”

A striking rise in the volume of digital images to be analyzed has accompanied the increasingly prevalent use of sophisticated medical imaging systems in cancer diagnostics. Automated CAD applications can assist in overcoming the logistical logjams that are created by a shortage of clinical radiologists, and support healthcare providers in offering patients earlier, more accurate detection and treatment.

Definiens' CAD applications employ contextual information to identify lesions and tumors smaller than the human eye can detect. The company's first commercially available CAD application will be released to European customers in early 2009, and will subsequently be submitted for U.S. Food and Drug Administration (FDA) approval for the United States market.

By automating image analysis, Definiens supports healthcare providers in analyzing and interpreting vast numbers of digital images accurately and consistently. The system improves the analysis of tissue samples and non-invasive imaging, enabling translational medicine, from early diagnosis to personalized treatment.

Definiens interprets images on every scale, from microscopic cell structures to satellite images. The Definiens Cognition Network Technology is an advanced and robust context-based technology designed to fulfill the image analysis requirements of the medical, life science, and earth science markets. The technology is modeled on the powerful human cognitive perception processes to extract intelligence from images. Definiens provides organizations with fast image analysis results, allowing deeper insights enabling better business decisions.

Related Links:
Definiens
New
Gold Member
X-Ray QA Meter
T3 AD Pro
New
Multi-Use Ultrasound Table
Clinton
New
X-ray Diagnostic System
FDX Visionary-A
New
Computed Tomography System
Aquilion ONE / INSIGHT Edition

Print article
Radcal

Channels

Radiography

view channel
Image: The new X-ray detector produces a high-quality radiograph (Photo courtesy of ACS Central Science 2024, DOI: https://doi.org/10.1021/acscentsci.4c01296)

Highly Sensitive, Foldable Detector to Make X-Rays Safer

X-rays are widely used in diagnostic testing and industrial monitoring, from dental checkups to airport luggage scans. However, these high-energy rays emit ionizing radiation, which can pose risks after... Read more

MRI

view channel
Image: The scans revealed a new dimension of brain network organization in humans (Photo courtesy of Georgia State University/TReNDS Center Research)

New Approach Identifies Signatures of Chronic Brain Disorders Using fMRI Scans

Traditional studies of brain function, often using fMRI scans to detect brain activity patterns, have shown promise in identifying changes in individuals with chronic brain disorders like schizophrenia.... Read more

Nuclear Medicine

view channel
Image: Example of AI analysis of PET/CT images (Photo courtesy of Academic Radiology; DOI: 10.1016/j.acra.2024.08.043)

AI Analysis of PET/CT Images Predicts Side Effects of Immunotherapy in Lung Cancer

Immunotherapy has significantly advanced the treatment of primary lung cancer, but it can sometimes lead to a severe side effect known as interstitial lung disease. This condition is characterized by lung... Read more

General/Advanced Imaging

view channel
Image: Cleerly offers an AI-enabled CCTA solution for personalized, precise and measurable assessment of plaque, stenosis and ischemia (Photo courtesy of Cleerly)

AI-Enabled Plaque Assessments Help Cardiologists Identify High-Risk CAD Patients

Groundbreaking research has shown that a non-invasive, artificial intelligence (AI)-based analysis of cardiac computed tomography (CT) can predict severe heart-related events in patients exhibiting symptoms... Read more
Copyright © 2000-2024 Globetech Media. All rights reserved.