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 Pediatrics
Endroit courant :
> This Story

Ouverture ou Registre to rate this News Story
Forward Printable StoryPrint Comment




MRI Homepage

MR and ultrasound biopsies combined can detect prostate cancers, says study Detect up to 33 percent more tumors together

Demand on the rise for MR-guided radiotherapy, says new report Compound annual growth rate of 20 percent through 2028

Breast MR for cancer survivors may result in unnecessary biopsies No difference in sensitivity compared to mammography alone

SEC probes Siemens, GE and Philips over business with China Lawsuit alleges OEMs worked together to fix prices on medical equipment

Ezra launches direct-to-consumer full-body MR scanning program Full-body imaging for $1,950 or single-region starting at $675

FDA okays Philips' MR-only radiotherapy simulator, MRCAT pelvis Create treatment plans for bladder, rectal, anal and cervical cancer

Bruker and the Champalimaud Foundation to develop first 18 Tesla UHF MR scanner Enable discovery of new contrast mechanisms

Whole body MR may support faster, less expensive cancer treatment planning A single scan for planning and staging, but challenges remain

Helium shortage could have deflating effect on MR industry Party City cites shortage as contributor to 45 stores closing

MR method could spare patients with skull lesions from CT, says study Could benefit children and pregnant women

A new AI system can detect
prostate cancer nearly as accurately
as experienced radiologists

AI comparable to radiologists in prostate cancer detection accuracy

par John R. Fischer , Staff Reporter
Researchers at the University of California, Los Angeles have developed a new AI system with a level of efficiency comparable to that of longtime radiologists in detecting prostate cancer.

Deemed FocalNet, the solution can identify and predict the aggressiveness of the disease, based on MR scans, with nearly the same amount of accuracy as radiologists with 10 years of experience. Its developers argue that the system could aid hospitals that are limited in their ability to supply the correct training necessary for radiologists to learn how to accurately identify benign and cancerous tumors and the grade of malignancies with multi-parametric MR.

Story Continues Below Advertisement


Special-Pricing Available on Medical Displays, Patient Monitors, Recorders, Printers, Media, Ultrasound Machines, and Cameras.This includes Top Brands such as SONY, BARCO, NDS, NEC, LG, EDAN, EIZO, ELO, FSN, PANASONIC, MITSUBISHI, OLYMPUS, & WIDE.

“Multi-parametric MR includes T2-weighted (T2w) MR, diffusion-weighted imaging (DWI) and dynamic contrast-enhanced MR (DCE-MR),” Dr. Kyung Sung, assistant professor of radiology at the David Geffen School of Medicine at UCLA, told HCB News. “This requires many years of experiences and volume to train, which may not be easy to implement for many hospitals.”

An artificial intelligence network, FocalNet utilizes an algorithm made up of more than one million trainable variables.

The researchers trained the system to assess and classify tumors consistently by feeding it MR scans from 417 prostate cancer patients and compare its findings to the actual pathology specimen.

Comparing its results with those of UCLA radiologists with more than 10 years of experience, the team found FocalNet to be accurate 80.5 percent of the time, compared to the radiologists at 83.9 percent.

They believe that with more training, the system could save on time and potentially become a diagnostic guide for less experienced radiologists.

“We anticipate the system would be improved when we include more training data sets, particularly from different MR scanners, and integration with patients' clinical information, such as clinical history and PSA scores,” said Sung. “It also can [detect] other cancers with MR, and we plan to expand its use to breast multi-parametric MR.”

The findings were published in IEEE Transactions on Medical Imaging, and were presented this month at the the IEEE International Symposium on Biomedical Imaging.

MRI Homepage

You Must Be Logged In To Post A Comment

La publicité d'email
Développez la notoriété de votre marque
Enchères + Ventes Privées
Obtenir le meilleur prix
Acheter des équipement / pièces
Trouver le meilleur prix
Infos du jour
Lire Les dernières nouvelles
Consulter tous les utilisateurs DOTmed
Éthique concernant DOTmed
Voir notre programme d'éthique
L'or partie le programme de fournisseur
Recevoir des demandes PH
Programme de marchand de service d'or
Recevoir des demandes
Fournisseurs de soins de santé
Voir tous les outils des HCP (abréviation pour les professionnels de la santé)
Trouver / combler un poste
Parts Hunter +EasyPay
Obtenir des devis de pièces
Voir les utilisateurs récemment certifiés
Voir les utilisateurs récemment certifiés
Récemment évalué sur DOTmed
Voir les utilisateurs récemment certifiés
Central de location
Louer de l’équipement à moindre prix
Vendre des équipements / pièces
Obtenir le maximum d'argent
Service Technicians Forum
Trouver de l'aide et des conseils
Simple demande de propositions
Obtenir des devis pour des appareils
Expo Virtuelle
Trouver des services d'appareils
L'Access et l'utilisation de cet emplacement est sujet aux modalités et aux conditions du notre de nos MENTIONS LEGALES & DONNEES PERSONELLES
Propriété de et classe des propriétaires DOTmedà .com, inc. Copyright ©2001-2019, Inc.