The worldwide market for automated breast ultrasound (ABUS) systems is expected to grow at a healthy compound annual growth rate (CAGR) of 8.1% to reach $212.4 million in revenues by 2025, according to a new report from market research and consulting firm Future Market Insights.
Growth will be driven mainly by the increasing prevalence of breast cancer, the growing radiology market, government breast cancer awareness campaigns, and extensive research and development for enhanced imaging techniques, according to the company. Other factors contributing to growth include strategic alliances among key vendors, manufacturers eyeing mammography market share, and expanding healthcare sectors in developing countries, Future Market Insights said.
The hospital segment will hold an estimated 54.2% market share in the global ABUS market by the end of 2015 and is projected to produce an 8.2% CAGR over the study period (2015-2025). Meanwhile, the diagnostic laboratories market sector is projected to climb at an 8.1% CAGR during the same time frame.
The firm said that North America will have a 42% market share by the end of the year and is expected to retain its dominant position throughout the study period. Europe is expected to hold a 32% share by end of 2015. The highest CAGRs between 2015 and 2025 will come from Japan and North America, driven by breast cancer prevalence and consumer concerns for early breast cancer detection in these regions, according to the company.
![A normal mammogram confirmed by three-year radiologic follow-up illustrates reader-marked regions of interest (ROIs) during (A) unaided (round 1) and (B) artificial intelligence (AI)–assisted (round 2) reading. Each colored dot represents an ROI for recall by a human reader. Readers could mark more than one ROI per case, represented by multiple dots of the same color. During AI-assisted reading, the AI system displayed three visible prompts: two with suspicion of malignancy scores of 35% (left mediolateral oblique [L MLO] and craniocaudal [L CC]) and one with a suspicion of malignancy score of 10% (right craniocaudal [R CC]), shown as polygonal overlays. Without AI, six of 10 readers (60%) marked a false-positive ROI. With AI assistance, this fell to two of 10 (20%). R MLO = right mediolateral oblique.](https://img.auntminnie.com/mindful/smg/workspaces/default/uploads/2026/07/2026-07-14-radiology-mammogram-ai-auto-bias.H0bYO8QlWs.jpg?auto=format%2Ccompress&fit=crop&h=100&q=70&w=100)
![A normal mammogram confirmed by three-year radiologic follow-up illustrates reader-marked regions of interest (ROIs) during (A) unaided (round 1) and (B) artificial intelligence (AI)–assisted (round 2) reading. Each colored dot represents an ROI for recall by a human reader. Readers could mark more than one ROI per case, represented by multiple dots of the same color. During AI-assisted reading, the AI system displayed three visible prompts: two with suspicion of malignancy scores of 35% (left mediolateral oblique [L MLO] and craniocaudal [L CC]) and one with a suspicion of malignancy score of 10% (right craniocaudal [R CC]), shown as polygonal overlays. Without AI, six of 10 readers (60%) marked a false-positive ROI. With AI assistance, this fell to two of 10 (20%). R MLO = right mediolateral oblique.](https://img.auntminnie.com/mindful/smg/workspaces/default/uploads/2026/07/2026-07-14-radiology-mammogram-ai-auto-bias.H0bYO8QlWs.jpg?auto=format%2Ccompress&dpr=2&fit=crop&h=167&q=70&w=250)
