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Synergyne Imaging Technology Inc. Publishes Breakthrough Research On AI-Based Endometrial Ultrasound Analysis
(MENAFN- EIN Presswire) EINPresswire/ -- Synergyne Imaging Technology Inc. is pleased to announce the publication of a landmark research paper in Discover Imaging, presenting significant progress in AI- and machine-learning-based automation for endometrial ultrasound analysis, a critical element in fertility diagnostics and embryo-transfer decision-making. This research was conducted in partnership with Cybera Inc., bringing together deep expertise in reproductive imaging and advanced computational modeling.
This peer-reviewed publication details the development of core AI/ML technologies that serve as foundational components within Synergyne's broader imaging innovation platform, AIM. These tools are components that meaningfully contribute to AIM's scientific infrastructure and ongoing evolution.
In this study, Synergyne and Cybera researchers applied modern computer-vision methods to:
-Identify and segment endometrial anatomy with expert-level precision.
-Measure endometrial thickness with sub-millimeter accuracy.
-Automatically classify endometrial pattern (trilaminar vs. homogeneous), representing the first published method of its kind.
The partnership with Cybera integrated Synergyne's clinical and imaging expertise with Cybera's advanced computational development capabilities, resulting in a rigorously validated model built on one of the largest known datasets of annotated endometrial ultrasound images.
Trained on 5,985 annotated ultrasound images, the system achieved accuracy exceeding 90% across all primary performance metrics, setting a new benchmark for automated endometrial assessment and outperforming previously published approaches.
“This research represents an important step forward in our scientific development pipeline,” said Steve Rowley, Vice President at Synergyne Imaging Technology Inc.“These AI/ML tools strengthen AIM's foundation and open the door to future applications.”
The findings reinforce Synergyne's long-standing commitment to developing high-precision, data-driven imaging solutions that enhance consistency, reduce subjectivity, and support standardized interpretation in medically assisted reproduction.
These technologies contribute to AIM's continuous quality improvement approach and provide a blueprint for future innovation in gynecologic imaging and reproductive health.
The full paper is available at:
About AIM
AIM is the next generation of the MatrisTM test-an AI-powered advancement in endometrial receptivity testing designed to enhance clinical efficiency and optimize fertility outcomes. AIM uses imaging and machine learning to deliver faster, more consistent, and personalized insights, empowering clinicians to make data-driven decisions that improve patient success.
For more information, visit aimfertility
This peer-reviewed publication details the development of core AI/ML technologies that serve as foundational components within Synergyne's broader imaging innovation platform, AIM. These tools are components that meaningfully contribute to AIM's scientific infrastructure and ongoing evolution.
In this study, Synergyne and Cybera researchers applied modern computer-vision methods to:
-Identify and segment endometrial anatomy with expert-level precision.
-Measure endometrial thickness with sub-millimeter accuracy.
-Automatically classify endometrial pattern (trilaminar vs. homogeneous), representing the first published method of its kind.
The partnership with Cybera integrated Synergyne's clinical and imaging expertise with Cybera's advanced computational development capabilities, resulting in a rigorously validated model built on one of the largest known datasets of annotated endometrial ultrasound images.
Trained on 5,985 annotated ultrasound images, the system achieved accuracy exceeding 90% across all primary performance metrics, setting a new benchmark for automated endometrial assessment and outperforming previously published approaches.
“This research represents an important step forward in our scientific development pipeline,” said Steve Rowley, Vice President at Synergyne Imaging Technology Inc.“These AI/ML tools strengthen AIM's foundation and open the door to future applications.”
The findings reinforce Synergyne's long-standing commitment to developing high-precision, data-driven imaging solutions that enhance consistency, reduce subjectivity, and support standardized interpretation in medically assisted reproduction.
These technologies contribute to AIM's continuous quality improvement approach and provide a blueprint for future innovation in gynecologic imaging and reproductive health.
The full paper is available at:
About AIM
AIM is the next generation of the MatrisTM test-an AI-powered advancement in endometrial receptivity testing designed to enhance clinical efficiency and optimize fertility outcomes. AIM uses imaging and machine learning to deliver faster, more consistent, and personalized insights, empowering clinicians to make data-driven decisions that improve patient success.
For more information, visit aimfertility
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