IMAGENDO study
Imagendo is a research study using AI and imaging to diagnose endometriosis
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About IMAGENDO
Express your interest for our ADIMAGENDO workshops
Express your interest for our ADIMAGENDO workshops
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Visit our Website
Latest Publications
The problem with the ‘truth’: rethinking ground truth for artificial intelligence in endometriosis diagnosis
The problem with the ‘truth’: rethinking ground truth for artificial intelligence in endometriosis diagnosis
Global trends in the uptake of specialist diagnostic ultrasound and MRI scans for endometriosis: An international cross‐sectional survey - Avery - International Journal of Gynecology & Obstetrics - Wiley Online Library
Global trends in the uptake of specialist diagnostic ultrasound and MRI scans for endometriosis: An international cross‐sectional survey - Avery - International Journal of Gynecology & Obstetrics - Wiley Online Library
Development of a Novel Machine Learning Model for Automatic Assessment of Quality of Transvaginal Ultrasound Images From Multi‐Annotator Labels - Deslandes - 2025 - Australasian Journal of Ultrasound in Medicine - Wiley Online Library
Development of a Novel Machine Learning Model for Automatic Assessment of Quality of Transvaginal Ultrasound Images From Multi‐Annotator Labels - Deslandes - 2025 - Australasian Journal of Ultrasound in Medicine - Wiley Online Library
Objectives Accurate diagnosis of pathology from ultrasound images is reliant upon images of a suitable diagnostic quality being acquired. This study aimed to create a novel machine learning model to...
Unpaired multi-modal training and single-modal testing for detecting signs of endometriosis
Unpaired multi-modal training and single-modal testing for detecting signs of endometriosis
ScienceDirect is the world's leading source for scientific, technical, and medical research. Explore journals, books and articles.
IMAGENDO News
Is surgery necessary for my endometriosis or ‘suspected’ endo?
Is surgery necessary for my endometriosis or ‘suspected’ endo?
Three years for diagnosis — even when she knew what was wrong
Three years for diagnosis — even when she knew what was wrong
It took Rachel Hosking three years to be diagnosed with endometriosis, now she is using AI to try reduce the time it takes for others to get diagnosed. SUBSCRIBE for the full story
Radio Health Journal Podcast with Dr Jodie Avery
Radio Health Journal Podcast with Dr Jodie Avery
Dr. Jodie Avery explains why America’s current process isn’t aiding women with this disorder.
IMAGENDO reported by ABC news- read the story!
IMAGENDO reported by ABC news- read the story!
A more accessible and less invasive way of diagnosing endometriosis could be available in clinics within the next two years following ground-breaking research out of the University of Adelaide.
IMAGENDO reported by ABC news- watch the story!
IMAGENDO reported by ABC news- watch the story!
Follow the latest headlines from ABC News, Australia's most trusted media source, with live events, audio and on-demand video from the national broadcaster.
Yuan Zhang and IMAGENDO in Computer Vision News
Yuan Zhang and IMAGENDO in Computer Vision News
Our Publications
Are sonographers the future 'gold standard' in the diagnosis of endometriosis?
Are sonographers the future 'gold standard' in the diagnosis of endometriosis?
Human–AI collaborative multi-modal multi-rater learning for endometriosis diagnosis
Human–AI collaborative multi-modal multi-rater learning for endometriosis diagnosis
Human–AI collaborative multi-modal multi-rater learning for endometriosis diagnosis, Wang, Hu, Butler, David, Zhang, Yuan, Avery, Jodie, Knox, Steven, Ma, Congbo, Hull, Louise, Carneiro, Gustavo
Intra- and interobserver agreement of proposed objective transvaginal ultrasound image-quality scoring system for use in artificial intelligence algorithm development
Intra- and interobserver agreement of proposed objective transvaginal ultrasound image-quality scoring system for use in artificial intelligence algorithm development
Non-invasive diagnosis of endo: Part 2
Non-invasive diagnosis of endo: Part 2
Endometriosis affects 1 in 9 women, taking 6.4 years to diagnose using conventional laparoscopy. Non-invasive imaging enables timelier diagnosis, reducing diagnostic delay, risk and expense of surgery. This review updates literature exploring the diagnostic value of specialist endometriosis magnetic resonance imaging (eMRI), nuclear medicine (NM) and computed tomography (CT). Searching after the 2016 IDEA consensus, 6192 publications were identified, with 27 studies focused on imaging for endometriosis.
Non-invasive diagnosis of endo: Part 1
Non-invasive diagnosis of endo: Part 1
AI as a teaching tool for gynae ultrasound
AI as a teaching tool for gynae ultrasound
Purpose The aim of this study was to investigate the current application of artificial intelligence (AI) tools in the teaching of ultrasound skills as they pertain to gynaecological ultrasound. Me...
Uncertainty-Aware Multi-modal Learning via Cross-Modal Random Network Prediction
Uncertainty-Aware Multi-modal Learning via Cross-Modal Random Network Prediction
Multi-modal learning focuses on training models by equally combining multiple input data modalities during the prediction process. However, this equal combination can be detrimental to the prediction accuracy because different modalities are usually accompanied by...
Deep Learning to diagnose POD obliteration with ultrasound
Deep Learning to diagnose POD obliteration with ultrasound
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