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AI enabled image analysis platform for scientific & medical imaging

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Why Zegami?

Zegami is unique because it easily works with both structured & unstructured data, from multiple sources: from images to documents and APIs to video. Based on Oxford University research, Zegami is being used by academics, researchers and commercial leaders across the world:
Researchers, scientists and engineers: The Plant Accelerator project at the University of Adelaide solves food supply issues in large automated greenhouses in Europe, Australia and the US, by giving researchers the ability to view thousands of images all at once on a screen, enabling them to spot patterns or anomalies in physiological and chemical traits.

Data scientists training machine learning models: Cancer Research UK funded project, developing a cancer detection system which identifies cancerous lesions in real-time by highlighting them on the video as the patient is being examined.
Data integration across silos: Companies such as Siemens, Honeywell and numerous other firms use Zegami to extract insights and answer questions from disparate data sources. This makes the process of data management and data cleaning faster, more efficient and gives them a competitive advantage.

The Zegami Solution for your Industry

Medical

Scientific

Machine Learning Data Curation

AI Lifecycle Management

Latest demo collections

DICOM Mammograms

This mammogram dataset consists of 3486 DICOM (Digital Imaging and Communications in Medicine) images. It contains normal, benign, and malignant cases with verified pathology information.

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The Muscle Atlas

The Muscle Atlas created for the Institure of Myology, Sorbonne University, contains over a thousand of muscle biopsy images from people of different ages as well as animals.

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COVID-19

COVID-19 lung X-ray insights. Cutting edge AI and visualisation technology can speed up efforts by researchers to develop new tools for diagnosis.

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Cancer Diagnosis

Oesophageal cancer video frames to find cancer lesions to train the machine learning model.

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Our Clients

“Using Zegami has delivered significant cost savings to APPF . Because of the nature of the experiments, problems with the apparatus can render several days’ of results unusable. With Zegami, a variety of subtle problems can be quickly identified and timely interventions made to correct them.”

APPF Australian Phenomics Facility

George Sainsbury

Data Architect and Software Engineer

“Without zegami I wouldn’t be able to feasibly accomplish my project in a reasonable amount of time. It just allows me to go through large amount of information in batches rather than individually and it is a complete game changer.”

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Lance Hentges

Researcher

Our Partners

Latest News & Events

Automated image and data clustering

We are excited to introduce our new feature – Automated image and data clustering! Besides offering a fascinating representation of the data, it provides some immediate practical benefits such as efficient labelling and rapid outlier detection.

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Stronger Together interview with Microsoft

In this interview with David Smith, Developer Advocate at Microsoft, our CEO Roger Noble explains how Zegami collaborated with the University of Oxford to analyse a research database of lung X-rays, and develop a machine learning model to identify cases of COVID-19.

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Roger Noble and Steve Taylor interviewed by Oxford Investment Consultants

Join OIC Principal and CFO Tania Wilson interview our CEO Roger Noble and CSO Steve Taylor.

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Let’s Talk

We’d love to understand the nature of your business or application, what data you have (both structured and unstructured), and help you visualise what’s possible with it.

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