NVIDIA CLARA Platform
Clara Medical Imaging is a collection of developer toolkits built on NVIDIA’s compute platform aimed at accelerating compute, artificial intelligence, and advanced visualization. Medical imaging industry is being transformed. A decade ago, the earliest applications to take advantage of GPU computing were image & signal processing applications.
Today, GPUs are found in almost all imaging modalities, including CT, MRI, X-ray, and Ultrasound bringing more compute capabilities to the edge devices. Deep Learning research in Medical Imaging is also booming with more efficient and improved approaches being developed to enable AI-assisted workflows.Today, most of this AI research is being done in isolation and with limited datasets which may lead to overly simplified models. Even when a fully validated model is available, it is a challenge to deploy the algorithm in a local environment. With the latest release of Clara AI for Medical Imaging now Data Scientists & Software/IT developers have the necessary tools, APIs and development framework to train and deploy artificial intelligence.
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NVIDIA Clara AI technology stack includes systems software libraries that form the foundation of GPU computing and abstracted software tools, containers, and workflow defining pipelines that allow data scientist and medical imaging developers to build and deploy AI for clinical workflows as well as accelerated research in Medical Imaging.
Clara Train SDK enables data scientists and medical researchers with state of the art tools and technologies that accelerate deep learning training for medical imaging.
The Clara Train SDK consists of two components:
AI-Assisted Annotation: Client APIs for integrating into DICOM viewers, this technology could enable radiologists to annotate much faster and eliminate the requirement for having to label every slice of CT and MRI data.
- DICOM viewers that integrate APIs would allow users to provide approximate points on image as input and return a list of slices already annotated for different organs leveraging the Deep Extreme Cut algorithm
- Annotation Client: example code demonstrates integrating SDK into third party applications showing API functionality. The Medical Imaging Interaction Toolkit (MITK) is a free open-source software system for development of interactive medical image processing software. Read more about MITK integrating NVIDIA AI assisted annotation DevNews article
- Domain specific Transfer Learning: Simplifies deep learning tasks such as segmentation of 3D CT/MRI images and enables researchers to train or fine tune models and export to NVIDIA TensorRT based inference with easy to use python wrappers.
- Also provided are several pre-trained models and applications. The 3-D Brain Tumor segmentation model developed by NVIDIA researchers won first place for Multimodal Brain Tumor Segmentation Challenge 2018. This and several other models developed by NVIDIA researchers are available to use with Clara Train SDK.
"We were able to get our hands on NVIDIA’s AI Assisted Annotation technology and integrate it into our viewer in a couple of days’ time. We currently annotate a lot of images - sometimes on the order of 1000 or more a day, so any technology that can help automate this process could potentially have a significant impact in reducing the time and cost of annotation. We are excited to leverage the AI assisted workflows and work with NVIDIA to solve these critical medical imaging problems."— Mark Michalski, Executive Director at MGH & BWH Center for Clinical Data Science
Clara Deploy SDK provides a container based development & deployment framework for building AI accelerated medical imaging workflows, it uses Kubernetes under the hood and enables developers and data scientists to define a multi-staged container based pipeline.The modular architecture allows developers to use the offerings of the platform end-end or customize the workflow pipelines with bring-your-own algorithms.
The capabilities forming the Clara Deploy SDK include:
- Data Ingestion interface to communicate to Hospital PACs system
- Cores services for orchestrating and managing resources for workflow deployment and development
- Reference AI applications that can be used as-is with user defined data or can be modified with user-defined-AI algorithms
- Lastly, Clara Deploy framework also includes Visualization capabilities to monitor progress and view final results
RabbitCT---an open platform for benchmarking 3D cone-beam reconstruction algorithms" Christopher Rohkohl, Benjamin Keck, Hannes G. Hofmann and Joachim Hornegger, Med. Phys. 36, 3940 (2009), DOI:10.1118/1.3180956 Download PDF - View BibTeX
- More cone beam CT research being done using CUDA than any other accelerator technology
- CUDA outperforms other accelerated technologies by an order of magnitude or more
- Most recent algorithmic developments being done are all CUDA accelerated
We specialize in accelerated medical image computing and guided surgery. NVIDIA’s Clara platform gives us the ability to turn 2D medical images into 3D and deploy our technology virtually.Wolfgang Wein, Founder and CEO
We are using AI to improve workflow for MRI and PET exams. NVIDIA’s Clara platform will enable us to seamlessly scale our technology to reduce risks from contrast and radiation, taking imaging efficiency and safety to the next level.Enhao Gong, Founder
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