See-Mode Technologies, an Australia-based medical technology company, has recently received regulatory approvals for its artificial intelligence (AI)-powered software that automatically analyses and reports breast and thyroid ultrasound scans in Australia and New Zealand. Such AI-backed innovations are expected to drive the growth of the Australian ultrasound systems market, says GlobalData, a leading data and analytics company.

Ultrasound imaging is one of the most extensively used medical imaging techniques in Australia and the world over. According to GlobalData’s analysis, the Ultrasound Systems market contributed about 14.8% of the Australian Diagnostic imaging market in 2022. GlobalData’s on-demand report, “Innovation in Healthcare: Ultrasound Imaging System”, provides detailed information regarding emerging disruptive innovations in the Ultrasound Imaging System.

Automation of ultrasound workflow provides significant benefits such as increasing consistency in image analysis and avoiding human errors in image interpretation. AI-backed See-Mode application will help in workflow automation. See-Mode uses advanced computational modeling techniques and deep learning to analyze medical images. It will help clinicians in the interpretation and analysis of clinical images improving the efficiency of workflow.

Dr. Satyajeet Salunkhe, Medical Devices Analyst at GlobalData, comments: “The integration of AI with ultrasound technologies will not only aid radiologists but also reduce turnaround time. Additionally, AI-backed analysis is expected to improvise diagnostic accuracy in the detection of breast and thyroid tissue abnormalities.”

For breast and thyroid tissues, See-Mode provides a classification of lesions in clinical images as per BI-RADS and TI-RADS rating systems which help in risk assessment and stratification. See-Mode will provide confidence to clinicians and may reduce unwanted thyroid biopsies. For breast tissue imaging, See-Mode will help clinicians identify potential lesions which may remain undetected in routine examinations. Additionally, the technology automates the identification of other vascular pathologies such as occlusion, refluxes, and stenosis.

Dr. Salunkhe concludes: “See-Mode represents a unique example of the implementation of AI to automate complex medical imaging analysis in routine clinical practice. Such AI-backed solution will not only reduce errors and provide accurate analysis of ultrasound images but also bring reliability in reporting and avoid instances of misclassification of ultrasound images.”