dismiss

Clean Sweep Live Auction on Wed. February 27th. Click to view the full inventory

DOTmed Home MRI Oncology Ultrasound Molecular Imaging X-Ray Cardiology Health IT Business Affairs
News Home Parts & Service Operating Room CT Women's Health Proton Therapy Endoscopy HTMs Mobile Imaging
SEARCH
Ubicación actual:
>
> This Story


Conexión o Registro to rate this News Story
Forward Printable StoryPrint Comment
advertisement

 

advertisement

 

Women's Health Homepage

Three decades of data clearly show mammography saves lives Breast cancer mortality statistics support benefits of mammo and early detection

Hologic launches Unifi Analytics to curb mammo downtime Predicting tube failures before they happen and setting performance benchmarks

Sarah Silverman calls out radiologist after bad breast screening experience 'Wear f**king GLOVES,' she wrote on Instagram, 'this isn’t a date'

Self-compression for breast cancer screening yields clinical advantages French study finds benefits in giving patients greater control

Mammo prior to breast reduction surgery may do more harm than good Researchers point to unnecessary follow-up, financial risk

New breast imaging modality may reduce unnecessary biopsies by up to 45 percent Combining ultrasound and near-infrared imaging

Putting the patient at the center of breast care Insights from Agnes Berzsenyi, president and CEO of GE Healthcare Women’s Health

Transforming the breast cancer screening experience with ready access to clinical data Breaking down barriers for better clinical outcomes

MobileODT deploys EVA System in first large-scale AI pilot for cervical cancer screenings Partnered with Apollo Hospitals and Genworks

Mammography screenings higher in coastal cities, says study Examined disparities in screening mammography utilization at city level

A new algorithm may be just as good
as an experienced mammographer
in interpreting breast density
says a study

Is AI a match for manual interpretation of breast density?

por John R. Fischer , Staff Reporter
A new algorithm designed to measure breast density may be just as accurate as an experienced mammographer, says a new study.

Breast imagers and AI experts at Massachusetts General Hospital (MGH) and Massachusetts Institute of Technology (MIT) have devised a new approach for automatically measuring breast density in an attempt to overcome the subjective discrepancies found in manual interpretations by different clinicians, and are using it at MGH in what marks the first example of a deep-learning mechanism of its kind to be implemented in clinical practice on real patients.

Story Continues Below Advertisement

GE Healthcare ultrasound probe solutions to help protect your investment

GE Healthcare helps reduce the downtime of ultrasounds with online access to probe and accessory purchasing, probe-failure diagnoses, fast repairs and replacements, probe care and handling tips, and reliable service options.



"Unfortunately, it is widely documented that radiologists' assessments of density are often inconsistent and highly subjective. Using machine computed density eliminates this inconsistency," Regina Barzilay, Delta Electronics professor of the Electrical Engineering and Computer Science Department at MIT, told HCB News.

The presence of dense breast tissue can mask tumors, preventing mammograms from detecting them and raising the risk of false negatives. Supplemental screening options, such as breast MR and ultrasound, though effective, may not be reimbursable and require expensive, out-of-pocket costs for patients.

Utilizing tens of thousands of high-quality, digital mammograms from MGH, researchers trained and tested the algorithm prior to implementing it in routine clinical practice. Eight radiologists then reviewed 10,763 findings determined by the model to be either dense or non-dense tissue, agreeing with its distinctions for 10,149 mammograms, the amount of which made up 94 percent of its total assessments.

Rejection of the other six percent, however, does not necessarily mean the algorithm was wrong when taking into consideration reader variability among radiologists. Barzilay says the next step is to develop technology that can predict future risks from images and combine those findings with those on breast density.

"While density correlates with risk, it doesn't on its own determine who is gonna get breast cancer," she said. "We are currently working on the algorithms that can predict future risk directly from images."

The researchers attribute the availability of high-quality, annotated data evaluations by radiologists and the collaborative efforts of experienced medical and computer science professionals as the key to the model’s success in clinical practice.

Approximately 16,000 images have been processed by the system since its implementation in January.

The study was published this month in the journal, Radiology.

Women's Health Homepage


You Must Be Logged In To Post A Comment

Anuncie
Aumente su conciencia de marca
Subastas + ventas Privadas
Consigue el mejor precio
Comprar Equipo/Piezas
Encuentra El Precio Más Bajo
Noticias diarias
Lee las últimas noticias
Directorio
Examina todos los usuarios DOTmed
Ética en DOTmed
Ver nuestro programa de ética
El oro parte programa del vendedor
Recibir las solicitudes de PH
Programa de distribuidor con servicio gold
Recibe solicitudes
Proveedores de atención de salud
Ver todos los HCP (abreviatura de asistencia médica) Herramientas
Trabajos/Entrenamiento
Encontrar/rellenar un trabajo
Parts Hunter +EasyPay
Obtener presupuestos para piezas
Certificado recientemente
Ver usuarios certificados recientemente
Recientemente clasificado
Ver usuarios certificados recientemente
Central de alquiler
Alquila equipos por menos
Vende equipos/piezas
Obtén más dinero
Mantenga el foro de los técnicos
Buscar ayuda y asesoramiento
Petición sencilla de propuestas
Obtén presupuestos para equipos
Feria comercial virtual
Encuentra servicio para el equipo
El acceso y el uso de este sitio está conforme a los términos y a las condiciones de nuestro AVISO LEGAL & AVISO DE LA AISLAMIENTO
Característica de y propietario DOTmeda .com, inc. Copyright ©2001-2019 DOTmed.com, Inc.
TODOS LOS DERECHOS RESERVADOS