Bringing Deep Learning To Digital Mammography.

Alixir is working on the mammographic detection system of the future, combining instant reporting with accuracy that exceeds a radiologist.

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More Accurate

More Accurate

Early studies of Alixir's breast cancer screening system have shown a sensitivity of over 95% and a specificity of 93% on a well-established segmented test set for digital mammography.

Faster

Faster

Alixir can segment a digital mammogram and provide customised reporting in seconds, expediting necessary callbacks and saving lives.

Cost Effective

Cost Effective

Alixir can augment or replace a human read, making the screening process more accurate and more cost effective than ever before.

Scalable Computer Vision In Digital Mammography

Alixir uses deep learning to segment and classify potential cancerous lesions on mammograms, leading to earlier detection and better patient outcomes. Our cloud infrastructure can easily integrate with PACS / BIS systems and enable scalable reporting on demand.

Scalable Computer Vision In Digital Mammography

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Meet the team

Dr. Joe Logan

Founder & CTO

Joe is the main tech guy here at Alixir, having over 25 years experience of programming and development, in addition to pursuing his PhD candidature at UTS in software engineering and AI.

He has vast experience of software engineering throughout the stack, and specialises in data science and machine learning implementation with Pandas, Hadoop, Python, Keras, PyTorch and TensorFlow.  He is also awesome with web and mobile frameworks such as React and Node, in addition to VR/AR development with C# and Unity.

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