3E Bioventures’ Post

#SubtleSYNTH is the industry's first AI-powered synthetic image generation solution. This regulatory milestone marks a new era and sets a new #SOTA for optimized MR acquisition and workflow. When combined with #SubtleMR, I have seen sites can experience up to a 70% reduction in scan time resulting in multiple times more happier patients. Congratulations to the entire team and all collaborators and supporters for advancing this next-gen AI solution. #SubtleAI

We have some very exciting news to announce today! Our AI-powered synthetic imaging software, SubtleSYNTH™, has received FDA clearance and is now available for clinical use in the US! 🚀 SubtleSYNTH™ uses deep learning to generate synthetic STIR images from already-acquired T1 and T2 weighted contrasts, creating STIR images with zero acquisition time that are interchangeable with conventionally acquired STIR images. This is an industry first, and we thank all of the members on the @SubtleMedical team and the clinical partners who helped us reach this milestone. This is just the start, as we explore plans to expand to Brain and MSK imaging next. Read the full press release below, and be sure to join us at RSNA this year to learn more about how SubtleSYNTH™ and our suite of imaging solutions can redefine your MRI imaging program. https://lnkd.in/g6Hr7uGC #AI #HealthcareInnovation #MedicalImaging #FDAcleared #SubtleSYNTH #SubtleMedical #MRI #Radiology #RSNA2023 #HealthcareTransformation

🚀 Exciting advancements in AI are transforming medical imaging!🚀 Deep learning-based image reconstruction (DLR) technology significantly enhances CT imaging for cardiac cases, reducing noise and radiation while maintaining image quality. Similarly, Body Vision Medical is applying AI in its LungVision® system to produce 3D tomographic images from standard C-arm X-ray images with the same benefits, namely enhanced image quality with reduced radiation dose. This AI Tomography® technology combined with other imaging functionality like augmented fluoroscopy ensures precise targeting during lung nodule biopsy and enables more efficient procedures, showcasing AI's broad potential to elevate diagnostic accuracy and patient outcomes across various imaging modalities. #AI #MedicalImaging #CT #Cardiology #LungBiopsy #Innovation #HealthcareTech #AdvancedBronchoscopy #LungCancer

📣 Medical Imaging Scientists & Engineers: Discover how you can perform 3D rendering and visualization, multimodal registration, and segmentation and labeling of radiology and pathology images. **Join us at the upcoming conference on June 5th to explore the latest advancements in medical imaging.** Medical Imaging Toolbox provides apps, functions, and workflows for designing and testing medical imaging applications. You can also train deep learning models for AI-enabled imaging applications. Click to learn more 🔗 Medical Imaging Toolbox For more details about the conference and to register, visit: https://lnkd.in/d64cyHxV #Medicalimaging #AI #Radiology

This Week: Join GE HealthCare's upcoming webinar: Staying Zoned In: "Unlocking the Potential of AI in Radiology", on Thursday, September 19. This special HIMSS roundtable features healthcare #AI experts, including Riverain’s Global Director-Channel Partnerships, Allen Hundley, who will share perspectives on navigating the complexities of integrating #AI into medical imaging workflows. Discover the crucial considerations for adopting and deploying AI algorithms, as well as examples of successful AI implementations, demonstrating improvements in diagnostic accuracy, workflow efficiency, and patient outcomes. Register here to join the conversation! ⬇️ https://lnkd.in/gzk38W9z #Radiology #webinar #Informatics #EnterpriseImaging #HIMSS

𝐂𝐓-𝐑𝐀𝐓𝐄 𝐚𝐧𝐝 𝐂𝐓-𝐂𝐋𝐈𝐏 𝐛𝐫𝐢𝐧𝐠 𝐚 𝐧𝐞𝐰 𝐀𝐈-𝐝𝐫𝐢𝐯𝐞𝐧 𝐦𝐞𝐭𝐡𝐨𝐝 𝐭𝐨 𝐦𝐞𝐝𝐢𝐜𝐚𝐥 𝐢𝐦𝐚𝐠𝐢𝐧𝐠, 𝐜𝐨𝐦𝐛𝐢𝐧𝐢𝐧𝐠 𝐚 𝐥𝐚𝐫𝐠𝐞 𝐝𝐚𝐭𝐚𝐬𝐞𝐭 𝐨𝐟 𝐜𝐡𝐞𝐬𝐭 𝐂𝐓 𝐬𝐜𝐚𝐧𝐬 𝐰𝐢𝐭𝐡 𝐚𝐝𝐯𝐚𝐧𝐜𝐞𝐝 𝐚𝐧𝐚𝐥𝐲𝐬𝐢𝐬 𝐭𝐞𝐜𝐡𝐧𝐢𝐪𝐮𝐞𝐬. This open-source project aims to enhance diagnostic processes and collabotration in medical imaging. This is a great example of how combining AI + Right Data + Healthcare can greatly improve patient outcomes. Preprint: https://lnkd.in/g_tF662a Dataset: https://lnkd.in/gSvtQ4HR Github: https://lnkd.in/gmebvadR #ai #genai #llm #MedicalImaging #AIHealthcare #OpenSource #HealthTech #Radiology #MachineLearning #DataScience #Innovation #DiagnosticImaging #AIInMedicine #FutureOfHealthcare

Join GE HealthCare latest episode of Staying Zoned In, "Unlocking the Potential of AI in Radiology", on September 19. In this special HIMSS roundtable, we're excited to welcome healthcare AI experts from Blackford Analysis Riverain Technologies and @Smart Reporting GmbH who will share perspectives on navigating the complexities of integrating AI into medical imaging workflows, as well as the key considerations for adopting and deploying AI algorithms. Register to join the conversation! https://lnkd.in/ef_pw8db #AI #Radiology #Informatics #EnterpriseImaging #HIMSS

This is Powerful ! A foundational model to segment any medical image 👇 9 months ago, Meta introduced SAM, a model able to segment any image. Despite its impressive performance on everyday images, SAM was not good at segmenting medical images, particularly the ones with weak boundaries and low contrast Segmentation of medical images is a core step of most AI pipelines in medical imaging. It is currently best performed by experts such as radiologists, but it is (very) time consuming, repetitive, error-prone and brain numbing 😵💫 We clearly need more automation for segmentation but medical images are complex and are very different from everyday images such as cats, dogs and cars This Canadian team developed further Meta’s SAM by fine tuning it on +1 million medical images (mostly CT, MRI and endoscopy) and built MedSAM, a foundational model for the « segmentation of a wide array of anatomical structures and lesions across diverse medical imaging modalities » This model did better than state-of-the-art segmentation foundation model and specialist models ! This is a major advance for medical AI With such models, we will expedite one of the most time and resource consuming step of building AI models in medicine, and it will probably accelerate the pace of innovation 🚀 Congrats and Thanks to the team behind MedSAM ! Bo Wang Jun Ma Vector Institute Peter Munk Cardiac Centre University of Toronto #AI #Radiology #Pathology #Segmentation #MedSAM #SAM Link to paper in the comment 👇

Recently, I attended a talk by Ricardo A Corredor J, from Siemens Healthineers, on the subject of Artificial Intelligence in Radiology and Microscopy. Ricardo highlighted AI's integration into CT scans, MRIs, and PET, emphasizing its potential to revolutionize medical imaging analysis. With tasks like image segmentation automated, AI boosts diagnostic accuracy and workflow efficiency, allowing healthcare professionals to focus more on patient care. Ricardo's talk painted a compelling vision of AI's future in healthcare, promising advancements in image reconstruction, disease detection, and treatment management. With AI as a trusted ally, we're poised for a future where healthcare delivery is more precise, efficient, and patient-centred. #AI #Radiology #Microscopy #HealthcareInnovation #MedicalImaging #FutureTech