What the Tech? Matrix AI Server Medical Diagnosis Services

A detailed look at Matrix’s AI Server Medical Diagnosis Services.

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For the past few months, the Matrix community has been able to interact and experiment with a couple of the Matrix AI Server’s basic features — namely, Matrix AI Pose Detection and Object Detection. Indeed, these two functions were the basis for a couple community competitions. While important building blocks in their own right, these two AI services barely scratch the surface of what is possible with the Matrix AI Server and its many AI services.

Artificial Intelligence Meets Medical Diagnosis

Active projects with these universities are primarily focused on small cell lung cancer and rib fracture detection. These projects rely on powerful AI models to analyze a litany of past cases, treatment guidelines and academic literature. The ultimate goal is to propose complete, appropriate treatment plans while simultaneously reducing the likelihood of missed- and misdiagnosis. This “leads to better care for patients, cost savings for insurers and suppliers, and larger data sets to improve AI-assisted diagnosis models,” adds Professor Deng.

The Small Cell Lung Cancer Project

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A preliminary flow for AI-enhanced imaging for small cell cancer lesions

The Matrix AI Server takes these high-resolution CT scans (20000 x 20000) and enhances them by analyzing macro- and micro-data. Doing so enables Matrix to identify SCLC cells, measure the tumor volume and complete an outline of the lesion.

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The Rib Fracture Project

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Rib Fracture Detection Flow

Matrix enables the diagnosis of fracture types, greatly improving the accuracy and efficiency of diagnosis and treatment. To this end, Matrix reconstructs the original CT scan and generates a 3D image. First, the patient’s spine and sternum are distinguished from the ribs using advanced morphology. Then, as each bone is segmented, the sternum and the spine are removed. Finally, any other bones are detected, and all ribs are uniquely identified. After identification, each rib is then individually matched to existing specialist-generated labels for the purpose of confirmation and fracture data is produced using VOC & COCO standards. Finally, the generated data is used to continuously train the AI models to identify an increasing number of fracture types.

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Generating 3D image of ribs

One thing that differentiates this approach from other methods is that, in order to solve the problems of unclear bone segmentation and sparse bone corrosion, Matrix uses advanced morphology and incremental learning throughout the analytical process. Simultaneously, in order to improve the efficiency in identifying individual ribs, Matrix uses code acceleration, interpolation algorithms and opencv.

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3D images of bone excision and of single rib with bounding box
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3D images of individual bones and ribs

The Future of AI-Medical Diagnosis

The Medical Diagnosis tools are accessible via the Matrix web wallet, under the AI Transaction tab.

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AI Transactions on the Matrix Web Wallet

To use the Matrix AI Server Medical Diagnosis services, simply upload the relevant files. In the case of SCLC, these should comprise an industry-standard set of medical images (dcm format). Once uploaded, click Generate Transaction.

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Exemplar of a CT scan, part of an industry-standard set

A full report will be produced and returned in about 15 minutes. Like all blockchain transactions, the results can be queried using the relevant Txhash. The Matrix AI Server analyzes the CT scans and generates a full report (downloadable as a pdf!). In this way, Medical Diagnosis transactions work in the same way as the AI Server Pose and Object Detection transactions.

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A full pdf report is generated by analyzing the CT scans

It should be noted that, currently, only the AI-enhanced imaging protocols to detect SCLCs is open to the public. The rib fracture protocol requires some more testing before the Matrix team releases it publicly.

Artificial Intelligence helps Matrix expand and deliver on the promise of blockchain. The team is very proud of their work on AI Medical Diagnosis services. Moving forward, Matrix — alongside its partners — will continue to train AI models using the Matrix AI Network’s excess computing power. In return, access to these AI models will be given to everyone. “The future of a secure, high-performance, and interoperable distributed computing infrastructure for AI is an important foundation for democratizing cost and access to AI modeling, effective public/private system integration, and helping AI scale and improve,” says Professor Deng. Matrix is democratizing artificial intelligence.

Matrix AI Network leverages the latest AI technology to deliver on the promise of blockchain.

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Owen Tao (CEO) | Steve Deng (Chief AI Scientist)

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Matrix AI Network leverages the latest AI technology to deliver on the promise of blockchain. Website: www.matrix.io Telegram: t.me/matrixainetwork

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