VOXELX ICO

ABOUT VoxeIX

VoxelX is a purely interactive and educative platform to bring a revolution in DICOM industry which is built to simulate Radiology. One of its main features is the ability to annotate and link structures and pathologies in the DICOM-images directly with all possible knowledge resources on the web. The content of thisplatform is community-based, so all members can share their pre-validated knowledge and cases either privately or publicly.

The VoxelX mission reconstructs interdisciplinary learning by creating an online platform for modeling DICOM medical training. The VoxelX team is one of the few that has worked since 2013 in the implementation of DICOM images in medical e-learning, especially in the field of radiology. The version of the DICOM-beta version of our platform was published on the Internet at www.voxelx.com in December 2016 at the annual meeting of the RSNA (Radiological Society of North America) in Chicago, USA.

We just published "VoxelX - DICOM-Platform is not an idea, it's a BETA product"
View integration https://twitter.com/Voxel_X with Blockchain here https://t.co/fmzYr7P24X
Go to http: / / /www.voxelx.com to use our DICOM Online viewer. Watch this video to learn how to link your DICOM to Pubmed using VoxelX

THE DICOM

DICOM (Digital Imaging and Communications in Medicine) is standard for storing and transmitting medical images enabling the integration of medical imaging devices such as scanners, servers, workstations, printers, network hardware, and picture archiving and communication systems (PACS) from multiple manufacturers. It has been widely adopted by hospitals, and is making inroads into smaller applications like dentists’ and doctors’ offices.

DICOM- PLATFORM

Our DICOM-platform is built to simulate radiology learning. It is purely interactive and educative. One of its main features is the ability to annotate and link structures and pathologies in the DICOM-images directly with all possible knowledge resources on the web. Implementing the blockchain in this platform will For teaching the user is allowed to build his own files for further use or lecturing, and this is aided by many auto recognition features like recognizing the same anatomical structure in a whole series and link it with the appropriate knowledge resource. Other features like social networking between the users, lecture presentation mode, tablet and mobile device mode, multi-touch capability, online case discussion, quick note system, have been implemented in the Tool.

Multidisciplinary learning is one of the most challenging tasks in medical education, on both the graduate and postgraduate levels. And as the volume of information in medical sciences grows rapidly, the demands on on this type of learning are getting bigger. VoxelX’s mission is to revolutionize the multidisciplinary learning by creating an online DICOM-platform to simulate medical learning. VoxelX’s team is one of the few that is working since 2013 in implementing DICOM-images in medical e-learning specially in radiology field. The content of this platform is community-based, so all members can share their pre-validated knowledge and cases either privately or publicly. And accordingly, by powering this platform with the blockchain we will be able to monetize the online content and create incentives to encourage radiologists both as publishers and validators in building and expanding the community of the platform. With the help of Ethereum’s ERC-20 tokens we were able to design rewards algorithm that pays radiologists for every single even tiny submission and update of the contents and images of the platform. VoxelX will be launching a token called GRAY and it will be used mainly to finance building the content of the DICOM-Platform.

Dynamically extracting, editing and showing multidisciplinary knowledge on every anatomical structure or pathology displayed in DICOM-images was the main goal of our online web-based DICOM tool. This direct integration between different online resources and the structure on the image can efficiently reduce time and effort needed for looking up any required information. While scrolling through the DICOM images, this tool allows learners to have full access to resources in our database or other external resources with a single click or a touch on a certain structure.

VoxelX platform is stuffed with many tools that enables the medical learner and the radiologist to interact easily with the DICOM-Images. Among these tools are innovative drawing tools that have made it possible to connect and link the structures and diseases on the images with all recognised knowledge resources on the web. The community of VoxelX is our real capital. We can divide this community according to the interest into learners, publishers and validators. All of them can interact with each other publicly or privately.

FEATURES OF Voxelx

• Social networking between users

• Lectures from the experts

• Tablet and mobile device mode

• Online case discussion

• Quick note system

• Ethereum wallet

• A drawing tool to make perfect pictures

• Gray tokens

VoxelX Tools
The platform is built to enable easy interactions and understanding of medical images (DICOM- images) for the medical learners.

VoxelX Community
The VoxelX community will be comprised of earners, publishers and validators. The community will be an interrelated community where all stand together. All interacting privately and publicly.

VoxelX Wallet
The platform is designed to create wallets for every user on the VoxelX wallet which is linked to the user's account. Also, it uses proof of work, which shows that the more contribution on the platform, the more tokens you get, coupled with the ranking system where users get rank according to their impact and contribution.

GRAY Token
A total of 10 billion grey token will be created. The gray Token will be distributed viz:

Token Sale - 45%
VoxelX Foundation - 25%
Early Investors and Bonuses - 10%
VoxelX Team and Founders - 20%

45% of the token will be sold during private, pre ICO and public sales. There will be discounts on tokens bought during the private and pre-ICO rounds.

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