Systems and methods for automated analysis of medical images

US11646119B2 · kind B2 · utility

Assignee

• Annalise-AI Pty LTD · AU

Inventors

• Dang-Dinh-Ang TRAN · Sydney, AU
• Jarrel SEAH · Sydney, AU
• David Huang · Melbourne, AU
• David Vuong · Piscataway, US
• Xavier Holt · Sydney, AU
• Marc Justin Nothrop · Sydney, AU
• Benjamin Matthew Austin · Sydney, AU
• Aaron Lee · Seoul, KR
• Marco Amoroso · Sydney, AU

Key dates

• Filing date: Jun 9, 2021
• Grant date: May 9, 2023
• Expiry date: Jun 9, 2041

Classification

• Technology area (CPC G): Physics
• CPC primary: G06T2207/30061
• WIPO field: Computer technology
• WIPO sector: Electrical engineering

Abstract

This disclosure relates to detecting visual findings in anatomical images. Methods comprise inputting anatomical images into a neural network to output a feature vector and computing an indication of visual findings being present in the images by a dense layer of the neural network that takes as input the feature vector and outputs an indication of whether each of the visual findings is present in the anatomical images. The neural network is trained on a training dataset including anatomical images, and labels associated with the anatomical images and each of the visual findings. The visual findings may be organised as a hierarchical ontology tree. The neural network may be trained by evaluating the performance of neural networks in detecting the visual findings and a negation pair class which comprises anatomical images where a first visual finding is identified in the absence of a second visual finding.