#Enterprise Imaging SolutionsInteroperabilityTeleradiologyEnterprise ImagingTeleradiology SolutionsVendor Neutral ArchiveEnterprise Workflow
Explore tagged Tumblr posts
Visit Tumblr Blog
Explore Tumblr blogs with no restrictions, modern design and the best experience.
Last Seen Tumblr Blogs
Fun Fact
Tumblr Inc. is using 66 technologies for its website.
Text
The Life of a Fhir Resource
v Raw
v Ingest
v Normalize
v Persist
v Analyze/Model
v Develop/Deploy
Source: https://www.dcmsys.com/.Information shared above is the personal opinion of the author and not affiliated with the website.
0 notes
Text
Facts To Know About Cloud Innovation in China
Ø Healthy China Initiative
Ø China is pushing to invest in strong health companies, especially domestically, while also developing their own research into solutions on providing healthcare for an aging population. Calls by Beijing to increase access to healthcare coverage while reducing coast barriers has brought on a significant increase in investments and the push fo innovation domestically. Cloud computing, telemedicine, artificial intelligence,and the substantial proliferation of diagnostic imaging are among the areas of focus.
Ø Expansion of Alibaba Cloud
Ø Alibaba has become the second largest cloud provider in the Asia Pacific only Amazon Web Services. According to CNBC, “ Alibaba is also helping Chinese companies that want to expand abroad and also increasingly winning business from large customers elsewhere that are looking to crack the china market, which has long been a challenge for outsider.”
Ø Doctor Shortage Paves Way for Telehealth Adoption
Ø The motivation for artificial intelligence growth and development could, in part, be explained by doctor shortages. Physicians report the need to automate some of their more repetitive work, and increase their availability, productivity, and workflow. According to a McKinsey Study, digitization impact up to 45% of revenue within the country’s healthcare industry.
Ø Growth in Utilization of Diagnostic Imaging
Ø China is dealing with an aging and rising population due to the implementation and abolishment of the one-child policy, respectively, setting the stage for an increase in the number of patients requiring high-value medical services such MRIs and CTs. China has a 5 year plan dedicated to providing imaging technology for rural hospitals.
Source: https://www.dcmsys.com/.Information shared above is the personal opinion of the author and not affiliated with the website.
0 notes
Text
Productivity Solutions Through DICOM Compression and Transfer Speed
Lossless and Lossy Compression and Transfer Speed Optimization
DICOM compression is one of most critical elements of your workflow protocols. Over a given Period, the amount of time from accumulated delays due to transfer issues has a direct impact on the level of revenue generated in that period: increased speed results in higher productivity. Higher productivity means more revenue.
But while DICOM compression speed is important, it isn’t everything. Image quality can also affect productivity. When images are insufficient for screening or diagnostic purposes, time must be taken to solve the problem. Lossless and Lossy compression solutions can provide complete or partial data, depending on the specific clinician requirement. With lossless compression, all of the original file data is intact after the file is uncompressed. Lossy compression, on the other hand transfers only relevant information during uncompression. With lossy compression, redundancy is eliminated. In many enterprises, both lossless and lossy transfers are needed to ensure high productivity and image quality.
When the attributes of speed and quality are combined, the speed of the digital file transfer correlates to the size of the compressed image. The compression ratios achieved by lossless compression techniques are less than lossy encoding techniques, which makes lossless encoding techniques unsuitable in certain situations.
That is why it is important to select a DICOM Compression vendor that has demonstrated success in both high speed transfers and image quality through lossless and lossy compression that can improve daily productivity and increase clinician, referrer and patient satisfaction.
Source: https://www.dcmsys.com/.Information shared above is the personal opinion of the author and not affiliated with the website.
0 notes
Text
Enterprise Imaging
Need Enterprise Imaging Solutions? Dicom Systems is a Health IT company offering a broad range of Enterprise Imaging Solutions including Interoperability and teleradiology workflow enablers. Log on https://www.dcmsys.com/interoperability/dicom-image-generator/
0 notes
Text
Automating Data De-identification
De-identification is a crucial aspect of attempts to advance medical technology at this, as billions of dollars find their way to firms promising huge bounds forward in Al for diagnosis in various fields.
Half of all surveyed chief information officers in health enterprises are planning to deploy artificial intelligence in some form either this year or next year. It’s a field with incredible potential, restricted by the essential need to protect patient’s personal information.
Any way of automating the data de-identification process will massively boost productivity and give the whole fields of medical Al a real shot in the arm.
Any Al that wants to learn even a minute amount about medical imaging needs to be fed a vast amount of data before it can be relied upon to make accurate assessments of medical imaging files. At a minimum, 100,000 samples are required. This enormous need for clean data renders manual attempts to de-identify medical files completely impractical.
Source: https://www.dcmsys.com/.Information shared above is the personal opinion of the author and not affiliated with the website.
0 notes
Text
Data De-identification
Automating Data De-identification
One aspect of medical technology innovation that is massively relevant to DICOM Systems at the moment is the concept of data de-identification. De-identification is a crucial aspect of attempts to advance medical technology at this time, as billions of dollars find their way to firms promising huge bounds forward in AI for diagnosis in various fields. Half of all surveyed chief information officers in health enterprises are planning to deploy artificial intelligence in some form either this year or next year. It's a field with incredible potential, restricted by the essential need to protect patients' personal information. Any way of automating the data de-identification process will massively boost productivity and give the whole field of medical AI a real shot in the arm.
The Necessity of Mass Data De-identification
Humans are in. a number of ways, easier to teach than artificial intelligence. That's because humans have been wired and conditioned over millions of years of evolution to recognize patterns, extrapolate, and intuit from incomplete data. AIs have a much shorter development time, and need to be taught from the ground up what conclusions they should draw from the data they receive. Since they haven't reached the level of sophistication necessary to teach them the flashes of human inspiration and intuition that serve many medical professionals so well, we have to resort to sheer brute force rote learning. Any AI that wants to learn even a minute amount about medical imaging needs to be fed a vast amount of data before it can be relied upon to make accurate assessments of medical imaging files. At a minimum, 100,000 samples are required. This enormous need for clean data renders manual attempts to de-identify medical files completely impractical. That's where we come in.
DICOM's Data De-identification System
DICOM does not itself deal in artificial intelligence algorithms, but we specialize in piping in the gallons of data needed to form a data lake from which an AI can draw to develop. To convert healthcare providers' imaging data into safe, de-identified data that the AI handlers can use, we have two scripts. The first works on the metadata of the file, finding and stripping out identifying information: 18 different kinds, including name, religion, and age. With this data securely eliminated, there is no way a patient can be identified from the metadata. The second script goes to work on the image file itself, neutralizing data (for example dates, patient number, hospital location etc.). There are several options that are available, depending on one's preference: scrambling identifying data in the file, or masking it entirely. It's important to note that, since the script goes to work on enormous sets of files indiscriminately, the data fed into it needs to be uniform. It can't detect if there are, for example data from two different hospitals with different notation policies, with five thousand images having their notations on the top, and five thousand having them on the right. It will merely scramble or mask the section of the image it is told to regardless of whether the notations are there or not. Be sure of the content of your image files before you set this script to work. Luckily, this process comes with its own QA stage, so as to ensure that any human oversights can be corrected before final dispatch.
Source: https://www.dcmsys.com/.Information shared above is the personal opinion of the author and not affiliated with the website.
0 notes
Text
Al In Healthcare
Interest in artificial intelligence (AI) is exploding!
Here are some predictions:
Al in health care will grow to $6.6 billion in a few short years, at a 40% annual compounded growth rate.
Al will enable an opportunity for $150 billion in industry savings.
What's Happening with Al Today?
Algorithms are replacing some clinical tasks.
Advances in clinical analytics and machine learning have the potential to drive medical discovery at a pace never seen before.
Al is also being used today to detect diabetic retinopathy in adults diagnosed with diabetes who had not previously received a diagnosis of diabetic retinopathy.
An AI Transformation Is Happening.
Source: https://www.dcmsys.com/.Information shared above is the personal opinion of the author and not affiliated with the website.
0 notes
Text
New Load Balancer Designed For Accelerated DICOM Application Performance
BENEFITS OF THE DICOM SYSTEM LOAD BALANCER
· Full configuration and management for optimized DICOM image caching, compression, Faster Application Delivery and scalability.
· Pre-Built, Easy to use templates for agile deployment in Enterprise Imaging.
· Provides an accurate, up-to-date health check on application and server performance.
· Available for a license as a standalone module or part of the DICOM Systems Enterprise Imaging Unifier Platform.
Source: https://www.dcmsys.com/.Information shared above is the personal opinion of the author and not affiliated with the website.
0 notes
Text
Enterprise Imaging Unifier and Archive Earns RSNA Image Share Validation
The Enterprise Imaging Workflow Unifier and Archive 3.4.12-1 assures customers that the system supports convenient, standards-based image exchange and has been shown to offer the following benefits to patients and providers:
· Improved efficiency.
· Cut Costs.
· Enhanced quality of care.
· Standards based interoperability to spur innovation.
· Eliminate CDs.
· Reduce radiation exposure.
· Expedite trauma workflows.
· Stop duplicative procedures
Source: https://www.dcmsys.com/.Information shared above is the personal opinion of the author and not affiliated with the website.
0 notes
Text
Deep Learning Medical Imaging
Ø Imaging Archive.
Ø De-Identify Images.
Ø Quality Assurance
Ø De-Identified Images.
Ø Deep Learning.
Ø Algorithm.
Ø FDA Clearance.
Source: https://www.dcmsys.com/.Information shared above is the personal opinion of the author and not affiliated with the website.
0 notes
Text
Teleradiology Solutions
Need Enterprise Imaging Solutions? Dicom Systems is a Health IT company offering a broad range of Enterprise Imaging Solutions including Interoperability and teleradiology workflow enablers. Log on https://dicomsystems.tumblr.com/post/164248485437/teleradiology-workflow
0 notes
Text
Vendor Neutral Archive
Need Enterprise Imaging Solutions? Dicom Systems is a Health IT company offering a broad range of Enterprise Imaging Solutions including Interoperability and teleradiology workflow enablers. Log on https://www.scoop.it/t/enterprise-imaging-solutions-1/p/4083152974/2017/08/16/enterprise-workflow-unifier
0 notes
Text
Teleradiology Workflow
Need Enterprise Imaging Solutions? Dicom Systems is a Health IT company offering a broad range of Enterprise Imaging Solutions including Interoperability and teleradiology workflow enablers. Log on https://www.dcmsys.com/interoperability/dicom-image-generator/
0 notes
Link
Need Enterprise Imaging Solutions? Dicom Systems is a Health IT company offering a broad range of Enterprise Imaging Solutions including Interoperability and teleradiology workflow enablers. Log on https://www.dcmsys.com/enterprise-imaging-solutions/dicom-secure-content-delivery/
0 notes
Text
How to Manage Data De-identification
Data de-identification is vital when handling patient imaging information for research or educational use.
● Quality Assurance - Any data de-identification methods must feature QA functions to ensure that protected healthcare information is verifiably de-identified before being shared outside a hospital’s infrastructure.
● Adaptive and Scalable - A de-identification system can’t be cookie-cutter, not with all the situations healthcare workers find themselves in. Any framework must be modifiable in liaison with clients in order to achieve the dual goals of producing useful imaging data while complying with HIPAA and Safe Harbor provisions.
● Third-party Reviewers - Before use, the system’s methodology, code, and data de-identification algorithms should be independently reviewed by objective third parties in order to ensure the integrity of personal data is preserved.
Source: https://www.dcmsys.com. Information shared above is the personal opinion of the author and not affiliated with the website.
0 notes
Text
Accelerating Application Performance across DICOM Networks
For DICOM traffic, efficiency can sometimes be a problem, especially when serving multiple locations.
● DICOM Load Balancer - Dicom Systems’ application-level load balancer offers a level of flexibility and sophistication which can improve IT resources across an enterprise.
● Distribution - The Load Balancer distributes traffic to ensure efficient use of servers.
● Multiple configurations - There are multiple configurations available for the Load Balancer to take into account available hardware, traffic levels, and other concerns.
● Positive response - Healthcare organizations seeking to accelerate DICOM performance have praised the Load Balancer for the high level of customization it offers. Its software updates and routing have also met with a high level of approval.
Source: https://www.dcmsys.com/2018/05/15/dicom-load-balancer/. Information shared above is the personal opinion of the author and not affiliated with the website.
0 notes