AI-Assisted
Neuro-Oncology

Every year, thousands of brain tumors are missed because of the limitations of human cognition, denying patients the best possible care.

With automated detection and tracking, our mission is to make cancer diagnosis and treatment faster and more precise.

1/3
of 17M new cancer patients per year will develop brain metastases
2-10
follow‑up brain MRI are required to monitor treatment response and identify relapses
1000+
images are reviewed for each MRI session
AFX Medical develops software solutions for identifying and tracking brain metastases
AFX-BM is intended to assist radiologists and radiation oncologists in their clinical workflow by integrating seamlessly with existing PACS infrastructure.
AFX-BM software solution

Detection and measurement

AFX-BM suggests the location of potential brain metastases on contrasted T1 brain MRI images.

Largest bidirectional diameters are automatically derived from the generated segmentation.

L: 12.3mmW: 9.4mm

Identify findings

Individual findings are listed along with their size for easy navigation.

Once approved, each finding is assigned a unique lesion label, persistent across studies.

Lesion 1Lesion 2Lesion 3Lesion 1Lesion 2Lesion 3

Longitudinal tracking

Approved findings corresponding to the same lesion are automatically associated between studies.

This association enables longitudinal tracking of individual lesion, facilitating estimation of clinical endpoints like RECIST or RANO-BM.

18/01/202315/02/2023Lesion 1Lesion 1

Comprehensive report

Detailed PDF report, concisely summarizing longitudinal data, including tables of tracked findings and graphical displays of lesion size progression.

first page of brain metastasis report second page of brain metastasis report

News

AFX Medical's aspiring AI technology transforms brain lesion detection in radiation oncology

In the heart of Montreal sits the non-profit organization Centech, a place that supports projects and startups with high growth potential – from conception right through to commercialization, which it says is thanks to a bold, collaborative, and passionate ecosystem.

2024-04-30
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AFX Medical featured at ALL-IN

As part of the Top 100 AI Startups, we were present at the 2023 ALL IN event to showcase our solution to the first edition of this important event dedicated to Canadian AI.

2023-09-27
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A second pair of eyes for radiation oncologists

The tool developped by AFX Medical and its partners discovers small brain tumors that were missed by a team of researchers in radio-oncology from the University of Montreal Research Center (CRCHUM). Findings were published at the Society for Neuro-Oncology congress annual meeting held in Tampa Bay, June 2022. [FR]

2022-11-30
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AFX Medical wins the Marika Zelenka Roy Innovation Prize at McGill CLIC 2022

The McGill Clinical Innovation Competition (CLIC) was launched in 2017 to inspire thinkers to develop solution that have a positive impact on healthcare. This award recognizes the best solution to an unmet clinical need for the care of a patient with the highest likelihood of success in being translated.

2022-11-25
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Using Ai To Prevent Cancer with Jeremi Lavoie, CEO @ AFX Medical | Tech for Good EP #13

On this week’s show, we spoke with Jeremi Lavoie, CEO @ AFX Medical Jeremi Lavoie is the Co-Founder and CEO of AFX Medical. He was General Manager of, Car2go group since 2013. He was legal counsel for Enercon from May 2012 to May 2013. He worked as a litigation attorney at the Attorney General of Quebec from May 2007 to August 2010. AFX Medical is an applied AI software company specializing in the detection of brain lesions in neuroimaging for oncology. Every year, thousands of brain tumours are missed on brain imaging because of the limitations of human cognition, leading to delayed cancer treatment. With automated detection, its mission is to make cancer diagnosis and treatment faster and more precise.

2022-03-02
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Incubators : startups with specific needs

Starting a business requires treading a path full of challenges, even more so when AI is involved. Thankfully, incubators are present to support young companies. [FR]

2022-02-18
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Research

6/27/2022
Automated Detection of Brain Metastases on T1-Weighted MRI Using a Convolutional Neural Network: Impact of Volume Aware Loss and Sampling Strategy
Detection of brain metastases (BM) and segmentation for treatment planning could be optimized with machine learning methods. Convolutional neural networks (CNNs) are promising, but their trade-offs between sensitivity and precision frequently lead to missing small lesions.
View publication
12/14/2022
The lost metastases: Deep Learning's Potential in Radiosurgery Quality Assurance
The multi-tier radiosurgery workflow at our institution left very few unidentified brain metastases (0.8%). Despite this low error rate, our AI algorithm still detected two lesions that required further treatment.
View publication
12/13/2017
Deep learning : A primer for radiologists
This review illustrates key concepts of deep learning necessary to understand its application to images, describes emerging clinical applications in radiology, and discusses technical requirements and future directions in this field.
View publication

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