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PITTSBURGH, June 01, 2017 (GLOBE NEWSWIRE) -- TeraRecon (www.terarecon.com), a leader in advanced visualization and enterprise medical image viewing solutions, today announced the acquisition of machine learning company, McCoy Medical Technologies, (www.mccoymed.com), at the Society for Imaging Informatics in Medicine’s Annual Meeting (SIIM17) in Pittsburgh, PA. Initially called WIA Corporation, a new company has been formed to provide simplified access to artificial intelligence (AI) algorithms with a focus on integrations that connect the work of individual end users, machine learning researchers, open source organizations and diagnostic imaging companies. The company’s products include a developer platform and a vendor neutral API interface for integration partners designed to streamline the distribution and hospital implementation of evidence-based practices and trained machine learning algorithms. The McCoy platform allows users anywhere to access cloud-based algorithms without requiring access to the algorithm code or training data to protect PHI and developer ­­­intellectual property. As part of the transaction completed earlier this week, the new independent company retains the McCoy Medical advisory board, including three world-leading imaging informatics experts and serial entrepreneurs: Dr. Eliot Siegel, Dr. Paul Chang and Dr. Khan Siddiqui. Dr. Siegel shared, “This decade has seen a proliferation of extremely impressive applications leveraging machine learning, especially for computer vision. Today, there is a real need for simpler, standards-based channels to socialize, access and apply these technologies. The TeraRecon and McCoy venture holds great potential to be among the first to develop and commercialize their offerings in the form of a truly open platform community. This kind of approach is exactly what is needed for the amazing innovations in AI to achieve widespread utilization.” Jeff Sorenson, TeraRecon President and CEO, said “The new company’s platform is open to everyone, from individual physician-inventors, to research institutions, and the world’s largest PACS vendors alike. Together, this new company becomes a catalyst to join the various AI communities together.” He continued, “Our goal is to incubate and accelerate a new kind of AI platform that allows a proven algorithm to be productized in 20 minutes.” Misha Herscu, McCoy CEO, commented, “This transaction results in a company with a unique combination of technology, healthcare-specific expertise and commercial reach. We look forward to meeting with potential collaborators and partners at SIIM17 and introducing these new possibilities.” The acquisition is aligned with the main interests of the SIIM17 conference attendees. The keynote address, titled “Harnessing Artificial Intelligence, Medical Imaging’s Next Frontier”, focuses on the potential impact of artificial intelligence on the medical imaging industry and the many uses of AI in healthcare. Visit WIA Corporation and TeraRecon June 1st-3rd during SIIM17 in Pittsburgh, Pennsylvania at Booth #603, as well as at the Society of Vascular Surgery’s 2017 Annual Meeting in San Diego, California at Booth #510. About McCoy Medical Technologies (www.mccoymed.com) McCoy Medical Technologies provides a developer platform and API interface for algorithm developers, partners and end users. McCoy facilitates the streamlined distribution and hospital implementation of evidence-based practices and trained machine learning algorithms via a vendor neutral distribution platform. The McCoy platform allows users anywhere to access cloud-based algorithms without requiring access to the algorithm code or training data to protect PHI and developer ­­­intellectual property. McCoy assists research institutions and emerging AI companies in the translational and commercialization processes, starting with rapid deployment via a scalable, secure, cloud-based infrastructure. McCoy also works with distribution partners, including TeraRecon, to make algorithms on the platform available to a very wide footprint of hospitals and, ultimately, to physicians. About TeraRecon (www.terarecon.com) TeraRecon is the largest independent, vendor neutral medical image viewing solution provider with a focus on advanced image processing innovation. TeraRecon’s solutions advance the accessibility, performance, clinical functionality and medical imaging workflow throughout many areas of the healthcare ecosystem. The company provides world class advanced visualization 3D post-processing tools, as well as a spectrum of enterprise medical image viewing, diagnostic interpretation, image sharing, cloud, interoperability and collaboration solutions. TeraRecon is a privately held company with its world headquarters in Foster City, California with major offices in Frankfurt, Germany; Tokyo, Japan; Acton, MA, and Durham, NC.


PITTSBURGH, June 01, 2017 (GLOBE NEWSWIRE) -- TeraRecon (www.terarecon.com), a leader in advanced visualization and enterprise medical image viewing solutions, today announced the acquisition of machine learning company, McCoy Medical Technologies, (www.mccoymed.com), at the Society for Imaging Informatics in Medicine’s Annual Meeting (SIIM17) in Pittsburgh, PA. Initially called WIA Corporation, a new company has been formed to provide simplified access to artificial intelligence (AI) algorithms with a focus on integrations that connect the work of individual end users, machine learning researchers, open source organizations and diagnostic imaging companies. The company’s products include a developer platform and a vendor neutral API interface for integration partners designed to streamline the distribution and hospital implementation of evidence-based practices and trained machine learning algorithms. The McCoy platform allows users anywhere to access cloud-based algorithms without requiring access to the algorithm code or training data to protect PHI and developer ­­­intellectual property. As part of the transaction completed earlier this week, the new independent company retains the McCoy Medical advisory board, including three world-leading imaging informatics experts and serial entrepreneurs: Dr. Eliot Siegel, Dr. Paul Chang and Dr. Khan Siddiqui. Dr. Siegel shared, “This decade has seen a proliferation of extremely impressive applications leveraging machine learning, especially for computer vision. Today, there is a real need for simpler, standards-based channels to socialize, access and apply these technologies. The TeraRecon and McCoy venture holds great potential to be among the first to develop and commercialize their offerings in the form of a truly open platform community. This kind of approach is exactly what is needed for the amazing innovations in AI to achieve widespread utilization.” Jeff Sorenson, TeraRecon President and CEO, said “The new company’s platform is open to everyone, from individual physician-inventors, to research institutions, and the world’s largest PACS vendors alike. Together, this new company becomes a catalyst to join the various AI communities together.” He continued, “Our goal is to incubate and accelerate a new kind of AI platform that allows a proven algorithm to be productized in 20 minutes.” Misha Herscu, McCoy CEO, commented, “This transaction results in a company with a unique combination of technology, healthcare-specific expertise and commercial reach. We look forward to meeting with potential collaborators and partners at SIIM17 and introducing these new possibilities.” The acquisition is aligned with the main interests of the SIIM17 conference attendees. The keynote address, titled “Harnessing Artificial Intelligence, Medical Imaging’s Next Frontier”, focuses on the potential impact of artificial intelligence on the medical imaging industry and the many uses of AI in healthcare. Visit WIA Corporation and TeraRecon June 1st-3rd during SIIM17 in Pittsburgh, Pennsylvania at Booth #603, as well as at the Society of Vascular Surgery’s 2017 Annual Meeting in San Diego, California at Booth #510. About McCoy Medical Technologies (www.mccoymed.com) McCoy Medical Technologies provides a developer platform and API interface for algorithm developers, partners and end users. McCoy facilitates the streamlined distribution and hospital implementation of evidence-based practices and trained machine learning algorithms via a vendor neutral distribution platform. The McCoy platform allows users anywhere to access cloud-based algorithms without requiring access to the algorithm code or training data to protect PHI and developer ­­­intellectual property. McCoy assists research institutions and emerging AI companies in the translational and commercialization processes, starting with rapid deployment via a scalable, secure, cloud-based infrastructure. McCoy also works with distribution partners, including TeraRecon, to make algorithms on the platform available to a very wide footprint of hospitals and, ultimately, to physicians. About TeraRecon (www.terarecon.com) TeraRecon is the largest independent, vendor neutral medical image viewing solution provider with a focus on advanced image processing innovation. TeraRecon’s solutions advance the accessibility, performance, clinical functionality and medical imaging workflow throughout many areas of the healthcare ecosystem. The company provides world class advanced visualization 3D post-processing tools, as well as a spectrum of enterprise medical image viewing, diagnostic interpretation, image sharing, cloud, interoperability and collaboration solutions. TeraRecon is a privately held company with its world headquarters in Foster City, California with major offices in Frankfurt, Germany; Tokyo, Japan; Acton, MA, and Durham, NC.


According to one embodiment, at least a portion of medical information of a patient is displayed within MRCS executed within a local device, the medical information including medical treatment history of the patient. At least a portion of the displayed medical information of the patient is transmitted to a medical imaging processing server over a network, where the transmitted medical information includes a patient identifier (ID) of the patient. Both the at least a portion of patient medical information and one or more medical images are displayed within the MRCS, where the medical images are associated with the patient and rendered by the medical image processing server. A set of icons representing a set of image processing tools is displayed within the MRCS, which when activated by a user, allow an image to be manipulated by the imaging processing server.


A medical information server receives a signal from a client device representing a first user interaction with first medical data associated with a first medical condition of a patient received from a first medical data server. A data retrieval module accesses a second medical data server to retrieve second medical data of the patient that is related to the first medical data. A data analysis module automatically performs a first analysis on image data of the first medical data to generate image quantitative result and a second analysis on the image quantitative result in view of other medical data of the patient to determine a likelihood of a second medical condition of the patient based on the analysis. A data integrator integrates the second medical data with an analysis result of the analysis to generate and transmit a view of medical information to the client device to be displayed therein.


SILICON VALLEY, CA and PARIS, FRANCE--(Marketwired - May 10, 2017) - Vizua (vizua3D.com) and Orange Silicon Valley are prototyping a new GPU-enabled Cloud. Based on Vizua's server computing patents and supercomputing platform from Orange Silicon Valley, the new Cloud will serve the emerging artificial intelligence (AI) and augmented reality (AR) applications in a wide range of industries. Because of increasing data and sophisticated algorithms for processing and display, the biggest challenge today for AI and AR applications is computing power. Additionally, investing in dedicated resources can be costly -- not only for upfront acquisition, but also maintenance and depreciation. And, dedicated resources often are not accessible to every device, everywhere, and make it difficult to share data and experiences. The new cloud prototype from Vizua/Orange Silicon Valley works towards addressing all these problems. The new cloud prototype provides high speed GPU enabled processing on-demand and is accessible to devices everywhere. A single server has supercomputing capability with 20 NVIDIA GPUs capable of supporting real time 3D rendering of 200 Microsoft HoloLens users. This supercomputing platform with optimized software from Vizua3D can handle over 10 times more users per GPU than a regular virtual machine (VM). It can also process extremely large files by optimizing the distribution over GPUs. Terabytes of data can be managed and loaded in a few seconds, and it is possible to launch a cloud service by leveraging such supercomputing infrastructure powered by the latest NVIDIA Pascal GPU architecture. Furthermore, the cloud based solution is designed to address a wide spectrum of markets: radiology, architecture, design, retail, industry, archeology, and gaming, to name just a few. In the medical field, TeraRecon, with its Within Image Analysis product (WIA™), is leveraging the supercomputing testbed infrastructure from Orange Silicon Valley to accelerate AI workloads. The prototype AI platform from Orange Silicon Valley allows WIA™ to boost performance for deep neural network based training, testing and application of the AI engine to improve clinical workflow as well as the diagnosis of patients. "We are very pleased to partner with the Orange Silicon Valley team," says Sylvain Ordureau, co-founder and CEO of Vizua. "Orange Silicon Valley and Vizua are prototyping a new HPC Cloud GPU platform to optimize the cost, performance and number of users per GPU to enable modern, intelligent applications in a wide variety of markets." "Deep Learning on hundreds of Tera Bytes of imaging data requires enormous computational capability and real time holographic rendering workloads with augmented cognitive capabilities are demanding when we scale to hundreds of users. Real-time 3D imaging combined with Artificial Intelligence powered inferencing capability will revolutionize medicine," says Georges Nahon CEO of Orange Silicon Valley. Vizua will be at GTC 2017 San Jose (CA) May 7-11 to demonstrate the power of their technology on the supercomputing server prototype from Orange Silicon Valley. Booth visitors can experience the Microsoft HoloLens and view shared virtual models projected on real objects with very high precision and incredible image quality. AI medical applications showcasing 3D printed medical models and TeraRecon software (terarecon.com) will also be demonstrated. About Vizua (vizua3D.com) - Vizua develops technology for the modern Cloud. Vizua's Cloud application platform can host any application and enables GPU-accelerated performance streamed to customers using standard HTML5 with significantly reduced cost compared to other solutions. The 3D suite from Vizua integrates with Vizua Cloud technologies, and offers a full range of features for 3D/VR/AR applications. Vizua is a privately held company based in Seattle, WA and was founded by industry veterans in technology and business. For more information, contact Sylvain Ordureau, Co-Founder/CEO, +1 (514) 424 8598/+33 6 20 52 10 91 About TeraRecon (terarecon.com) - TeraRecon is the largest independent, vendor neutral medical image viewing solution provider with a focus on advanced image processing innovation. TeraRecon iNtuition and iNteract+ solutions advance the accessibility, performance, clinical functionality and medical imaging workflow throughout many areas of the healthcare ecosystem. The company provides world class advanced visualization 3D post-processing tools, as well as a spectrum of enterprise medical image viewing, diagnostic interpretation, image sharing, interoperability and collaboration solutions. TeraRecon is a privately-held company with its world headquarters in Foster City, California with major offices in Acton, MA, Durham, NC, Frankfurt, Germany and Tokyo, Japan. About Orange Silicon Valley (http://www.orangesv.com/) - Orange Silicon Valley (OSV) is the wholly owned innovation subsidiary of Orange SA, one of the world's leading telecommunications operators, serving 265 million customers across 29 countries. Through research, development, and strategic analysis, Orange Silicon Valley actively participates in the disruptive innovations that are changing the way we communicate. OSV contributes to and engages with the regional Silicon Valley ecosystem through numerous programs, such as our Orange Fab startup accelerator, Orange Institute, and ongoing collaborations with partners. Orange Silicon Valley acts as a guide to the digital revolution occurring in the San Francisco Bay Area, regularly hosting startups, businesses, and corporate leadership from around the world.


A cloud server receives a request for accessing medical image data from a client device, where the cloud server provides image processing services to users in image processing steps, resulting in image views. User privileges of a user are determined for accessing the medical image data. In response to receiving a command having a selection of an image view from the client device, the cloud server provides the medical image data based on the selected one or more image views. The user interactions of the user with the medical image data via the selected image views are tracked, including tracking how long in time the user has spent on a particular image view. An analysis is performed on the tracked user interactions to determine an overall usage trend of the image views.


According to one embodiment, at least a portion of medical information of a patient is displayed within MRCS executed within a local device, the medical information including medical treatment history of the patient. At least a portion of the displayed medical information of the patient is transmitted to a medical imaging processing server over a network, where the transmitted medical information includes a patient identifier (ID) of the patient. Both the at least a portion of patient medical information and one or more medical images are displayed within the MRCS, where the medical images are associated with the patient and rendered by the medical image processing server. A set of icons representing a set of image processing tools is displayed within the MRCS, which when activated by a user, allow an image to be manipulated by the imaging processing server.


According to one embodiment, at least a portion of medical information of a patient is displayed within MRCS executed within a local device, the medical information including medical treatment history of the patient. At least a portion of the displayed medical information of the patient is transmitted to a medical imaging processing server over a network, where the transmitted medical information includes a patient identifier (ID) of the patient. Both the at least a portion of patient medical information and one or more medical images are displayed within the MRCS, where the medical images are associated with the patient and rendered by the medical image processing server. A set of icons representing a set of image processing tools is displayed within the MRCS, which when activated by a user, allow an image to be manipulated by the imaging processing server.


According to one embodiment, workflow templates are stored, each including a predefined sequence of workflow stages associated with a particular type of medical diagnosis or process. Each workflow stage defines one or more image processing operations to be performed. At least one workflow stage generates metadata specifying a parameter to be used by another workflow stage for processing a corresponding medical image. In response to medical image data received, at least one of the image processing operations defined by the workflow stages is performed on the medical image data. A scene is generated for each of the workflow stages representing an image view representing the medical image data. In response to a save or validate command received from a user, the scene associated with each of the workflow stages is stored in a persistent storage, which can be used to recreate a corresponding medical image view subsequently.


According to one embodiment, workflow templates are maintained, each workflow template including a predefined sequence of workflow stages associated with a particular type of medical diagnosis or process. In response to a request for processing medical image data from a user, a user identifier (ID) that identifies the user is automatically determined based on the request. At least one of the workflow templates that is specifically configured to process medical image data associated with the user is identified based on the user ID. One or more image processing operations defined by the identified workflow template are performed on the medical image data, generating a scene corresponding to an image view representing the medical image data. The scene associated with each of the workflow stages is stored in a persistent storage, where a scene includes metadata used to recreate a corresponding medical image view subsequently.

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