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The platform is transforming how radiologists and clinicians leverage AI by making it accessible to everyone. It offers an intuitive, browser-based annotator that integrates seamlessly with the latest picture archiving solutions (PACS). The integrations allow clinicians to annotate medical images directly in the browser and start training AI models with as few as five images. The user-friendly design and rapid deployment capabilities ensure that any clinician, regardless of technical background, can develop AI models for diverse applications, ranging from diagnostics to 3D modeling.
“There is a lot of repetition in radiology. Yet, only a small fraction of the tasks are automated as AI companies struggle to keep up with the huge unmet clinical needs,” said Pieter De Backer, MD, PhD, MScEng, Co-Founder of Medannot. “We’ve fundamentally changed the approach by enabling clinicians to become the AI developers themselves. With our platform, they can create, train, and deploy AI models tailored to their specific needs, allowing them to address these gaps more effectively and at an unprecedented pace.”
Medannot already features an AI store with more than 50 AI models, offering a wide range of capabilities to enhance radiology workflows. Notable examples include an AI model for detecting lung cancer in CT scans, a tool that automates the segmentation of maxillofacial bones and surrounding tissues to facilitate the precise identification of vessels for grafts and flaps in reconstructive surgeries and an AI that allows for non-invasive colonoscopies using Medannot’s Virtual Reality features.
The platform was also recently utilized to guide 3D robotic surgery in a clinical trial. In this trial, an auto-generated 3D surgical model was overlaid using augmented reality directly within the robot's video feed as a reference.
Clinicians using Medannot can collaborate on the development and multicentric validation of these AI models, ensuring their effectiveness in real-world clinical settings. The platform also provides the required regulatory infrastructure and takes charge of the certification process, using the clinical evidence built by the community to guide these models through FDA and MDR approval. Finished models can be listed in the AI store, allowing clinicians who created or helped validate them to financially profit from their use.
“This collaborative approach accelerates the development and adoption of AI in radiology and provides a new revenue stream for clinicians and hospitals, empowering them to contribute directly to the advancement of medical technology,” adds MScEng. Robert Klein, Co-Founder & CTO.
“The investment from Zero One Hundred underscores their dedication to advancing healthcare innovation,” said Martin Herman, a Board Member at Medannot, who has partnered with Zero One Hundred on another successful medical startup Powerful Medical, a medical device manufacturer specializing in AI-powered ECG diagnostics. He further emphasized the value of their support. “Zero One Hundred has been a steadfast and reliable partner, particularly in ventures that challenge and redefine medical technology.”
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