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Intel White Paper on AI-Based Diagnostic Imaging with Hitachi and Intel® DevCloud

Summary

Accelerate advanced diagnostics with Intel DevCloud for the Edge, a cloud-hosted sandbox designed for medical developers. This platform allows healthcare organizations to quickly prototype and test deep learning algorithms vital for analyzing complex modalities like CT, MRI, and X-ray scans directly at the point of care. Ideal for clinicians and enterprise partners, it supports the seamless integration of AI intelligence into existing edge infrastructure, ensuring faster time-to-market for next-generation diagnostic systems and improving patient care delivery through reliable, scalable computing solutions.

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Solution brief Intel® Dev Cloud for the Edge

Hitachi Speeds AI-Based Diagnostic Imaging with Intel® Dev Cloud for the Edge

Developing targeted algorithms for advanced modality systems enhances healthcare at the edge

“Because developers can quickly The healthcare sector is experiencing significant changes—from aging demographics and a prevalence of lifestyle diseases to regional disparities in care provision and

evaluate the performance of

the rising cost of public healthcare. At the same time, continual growth in the already

their applications in multiple

vast amount of healthcare data requires advanced compute performance and edge computing systems by capabilities and more efficient processing, not just in the cloud and data center, but increasingly at the edge.

using Intel® Dev Cloud for the Edge, they can not only shorten Vision is at the core of much healthcare data the inspection time to go to

Healthcare use cases and services at the edge—combined with new digital care market, they can also expect models supported by smart devices, cameras, network video recorders (NVRs), and sensors—are generating more and more unstructured visual data. Diagnostic

tremendous benefits in terms

and medical imaging also rely on visual compute technologies and AI inference

of investment and maintenance

for analysis. Increased use of analytics in healthcare networks requires more in verification equipment. advanced, flexible ways of assessing and managing visual data to ensure clinicians and organizations are extracting maximum and timely value.

“We are confident that Intel

Meeting new infrastructure demands

Dev Cloud for the Edge will

The need for broad collaboration between physicians, specialists, and pharma to

accelerate and streamline

help ensure a holistic view of patient care places new demands on existing edge

operations and create new value

computing infrastructure. Tightly coupled OS, firmware, and hardware can make for our customers.” adding or changing functions difficult and costly. Diagnostic imaging systems, such as MRI and CT scans, have advanced significantly,

—Tomohiro Nagao, Senior Manager,

Solution Business Division, featuring scanning technology with greater accuracy and sophisticated capabilities

Diagnostic Systems Division, for data analysis and interface optimization.

Hitachi, Ltd., Healthcare Business Unit

Bringing advanced analysis to modality systems Hitachi is augmenting and enhancing image analysis and diagnostic features leveraging AI and deep learning algorithms for modality systems, including CT scan, MRI, X-ray, and ultrasound. Hitachi initially considered using GPU-based systems for the AI enhancements, but a product feasibility study found a negative impact on cost and power/heat dissipation. Hitachi sought to accelerate development time by leveraging AI and targeting smoother integration and fusion of AI and non-AI algorithms by Intel® Distribution of Open VINO™ toolkit.

Page Summary Contents For Intel White Paper on AI-Based Diagnostic Imaging with Hitachi and Intel® DevCloud

Page 1 Solution brief Intel® Dev Cloud for the Edge Hitachi Speeds AI-Based Diagnostic Imaging with Intel® Dev Cloud for the Edge Developing targeted algorithms for advanced modality systems enhances healthc...
Page 2 Solution Brief | Intel® Dev Cloud for the Edge Intel® Dev Cloud for the Edge provides a Healthcare intelligence at the edge sandbox for fast testing and prototyping Intel and its ecosystem partners ar...

Manual Details

Brand Hitachi
Pages 2
File Size 304.77 KB
Published June 05, 2026
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Frequently Asked Questions

What is the learning curve for using DevCloud and the OpenVINO toolkit?

The learning curve for Intel DevCloud for the Edge and the Intel Distribution of the OpenVINO toolkit is minimal.

How can Intel DevCloud assist in integrating AI diagnostics into medical imaging systems?

It provides a flexible software development environment supporting multiple edge devices, applications, and services on a single common platform.

What processor families are utilized for necessary scalability and performance improvements?

High-performance options include the Intel Xeon Scalable processor family and the Intel Core processor family.

How did using DevCloud enable Hitachi to refine their solutions faster?

The company was able to accelerate prototyping and testing, which allowed them to innovate and speed time to market for their deep learning inference solutions.