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
SEARCH
当前地点:
>
> This Story

starstarstarstarstar (1)
注册记数器 to rate this News Story
Forward Printable StoryPrint Comment
advertisement

 

advertisement

 

X-Ray Homepage

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

FDA greenlights Samsung S-Vue 3.02 dose reduction solution Reduces X-ray dose exposure for pediatric patients

DR now makes up over 80 percent of US general radiography install base Up from only half in 2015

FDA clears GE’s AI-based CT image reconstruction technology Available as upgrade to Revolution Apex scanner

Philips Medical Systems sues ex-employee over alleged secrets theft Suit claims X-ray tube trade secrets were stolen before erasing hard drive

The upper extremity value of mini C-arms in the ER and OR Insights from Dr. Korsh Jafarnia

X-ray sheds new light on ancient mummy The Everhart Museum in PA tapped Geisinger Radiology for help

First ultra high-res CT scan performed on US patient Scanner at UC Davis can image anatomy as small as 150 microns

Joint Commission fluoro mandate may confuse providers, say experts Requires max exposure rates of imaging modes for fluroscopy devices

This UK company is utilizing space technology to develop a portable 3D X-ray system Adaptix has received $1.35 million from space agencies

Will computers replace radiologists?

John W. Mitchell , Senior Correspondent
In the next ten years, computers could be reading the majority of routine diagnostic imaging tests such as mammograms and chest X-rays. This could allow radiologists to spend their time sorting out abnormal findings, conducting invasive procedures, and spending more time with patients.

That’s the prediction of a physician expert who presented a webinar titled “Deep Learning: How It Will Change Everything”, organized by the Society for Imaging Informatics in Medicine (SIIM) and attended by nearly 300 people on Wednesday.

Story Continues Below Advertisement

New & Refurbished C-Arm Systems. Call 702.384.0085 Today!

KenQuest provides all major brands of surgical c-arms (new and refurbished) and carries a large inventory for purchase or rent. With over 20 years in the medical equipment business we can help you fulfill your equipment needs



“Deep learning is the hot area,” Dr. Bradley J. Erickson, M.D., Ph.D., professor of radiology and associate chair for research at the Mayo Clinic told HCB News. “Physicians may say they have information that may not be computable ... but deep learning allows imaging reading by computers that see more than we see.”

Erickson explained that deep learning is the next step after traditional machine [computer] learning. In machine learning an algorithm finds features – or things that are measured – and then learns a correct answer.

Deep learning automates both of these steps to make the findings faster and with greater accuracy. He noted that deep learning research has improved machine interpretation applications from a degree of error of around 25 percent in 2011 to less than four percent in 2015.

He also said that a criticism of deep learning is that it required millions of samples to be accurate. But Erickson “busted that myth” by presenting several research cases in which as little as tens of imaging samples were used to accurately make clinical findings.

“Machine learning is objective,” he stressed. “Its decisions are based on data.” Erickson added that machine learning is also pervasive, meaning it can be applied to images 24 hours a day (including holidays and weekends) from underserved areas as easily as in major metropolitan cities.

Deep learning still has a way to go and would be subject to FDA approval as a new medical device.

“Its use today is still limited,” Erickson said. “But I think that reports showing it can find textures and patterns in MRI images that reflect genomic properties that are not visible shows the power and promise of applying machine learning in medicine.”

Advancements are accelerating, especially in the past two years. He added that advancements in the next two years will be even more exciting. He attributed this to the exponential growth in computing and algorithmic capability, much of it developed by the gaming industry.

“Bill Gates said we always overestimate what we can do in two years, and underestimate what we can do in ten,” Erickson said. “I think that will be the case for machine intelligence applied to medical images.”

He also said that for deep learning to be successful, radiologists must embrace this new technology.

“Physician engagement has to part of this revolution,” he added. “We want the computers to be the underlords (serving physicians and patients), not the overlords (ruling physicians and patients).”

X-Ray Homepage


(1)

Jorge Cejudo

Will Radiologists use another Sense?

August 25, 2016 10:43

I am sure computers will improve the work of Radiologists, leaving them more time to spend on incidental findings or non standard diseases. That's why we have been researching and get some advantages improving Diagnostic using the Hearing Sense. Check it out: www.auding.org

Log inor Register

to rate and post a comment

You Must Be Logged In To Post A Comment

做广告
提升您的品牌知名度
拍卖+私人销售
获得最好的价格
买设备/配件
找到最低价格
每日新闻
阅读最新信息
目录
浏览所有的DOTmed用户
DOTmed上的伦理
查看我们的伦理计划
金子分开供营商节目
接收PH要求
金子服务经销商节目
接收请求
提供保健服务者
查看所有的HCP(简称医疗保健提供商)的工具
工作/训练
查找/申请工作
Parts Hunter +EasyPay
获取配件报价
最近证明
查看最近通过认证的用户
最近额定
查看最近通过认证的用户
出租中央
租用设备优惠
卖设备/配件
得到最划算
服务技术员论坛
查找帮助和建议
简单的征求建议书
获取设备报价
真正商业展览
查找对设备的服务
对这个站点的通入和用途是受期限和条件我们支配 法律公告 & 保密性通知
物产和业主对 DOTmed.com,公司 Copyright ©2001-2019 DOTmed.com, Inc.
版权所有