01 Integration of Ai and Machine Learning The integration of artificial intelligence (AI) and machine learning (ML) is revolutionizing the global market by enhancing diagnostic accuracy, reducing image processing time, and enabling precision medicine. These technologies assist in automating image interpretation, reducing human error, and improving clinical workflows. AI-based tools are being increasingly incorporated into PET, CT, and MRI systems for more effective disease detection and prognosis. For instance, in June 2024, a novel AI tool was revealed at SNMMI 2024 that uses deep transfer learning to automatically segment and quantify wholebody PET/CT scans, detecting six cancer types, including lung, melanoma, lymphoma, breast, headandneck, and prostate. It estimates tumor burden, predicts treatment response and risks, enabling prognosis and survival assessment with strong performance. As AI becomes more sophisticated, it is expected to significantly expand clinical applications in oncology, neurology, and cardiology.
September 2025 Koninklijke Philips expanded its molecular imaging capabilities through advancements in PET/MR and digital imaging technologies, supporting improved disease detection and personalized treatment planning.
July 2025 United Imaging Healthcare expanded its molecular imaging portfolio with new PET/CT system developments, strengthening its presence in oncology, neurology, and cardiovascular diagnostic imaging applications.
June 2025 GE HealthCare expanded its molecular imaging solutions by introducing enhancements to its PET imaging platforms, incorporating advanced digital technologies to improve image quality, quantitative analysis, and clinical workflow.
May 2025 Siemens Healthineers expanded its molecular imaging portfolio with advancements in PET/CT and SPECT imaging technologies, focusing on improved diagnostic accuracy, workflow efficiency, and support for precision medicine applications.