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The discussions emphasize the transformative potential of the research, with comments like 'game changer if/when it pans out' and 'tremendous promise,' which indicate excitement about future possibilities. The tone is optimistic, and the references to GANs and low-dose imaging suggest a focus on technological advances and their significance for patient care, fostering a sense of deep engagement and anticipation among participants.
Most discussions express strong support or enthusiasm for the research, using words like 'tremendous promise,' 'game changer,' and 'proof of concept,' indicating a high level of agreement on its significance.
Posts demonstrate high curiosity and relevance, with many highlighting the potential to reduce contrast agents and mentioning specific techniques like GANs and low-dose imaging, reflecting keen interest.
Several comments delve into the technical implications, such as GAN recovery and lesion detection, showing deep engagement with the research's methods and potential applications.
The discussions suggest that the publication could have a meaningful impact on medical imaging practices, though some posts mention it as a promising proof of concept rather than an immediate breakthrough, indicating perceived high but cautious impact.
#RADIOLOGY AI generated low dose breast MRI https://t.co/d0u2ilQsYR @radiology_rsna @ProfKuhl #breastradiology #breastmri #mri https://t.co/HpDUgrFGBy
Using a training set of standardized contrast-enhanced breast MRI scans, GANs recovered image appearance and conspicuity of enhancing lesions from simulated low-contrast images, as verified on independent test sets. https://t.co/2hPbOHPNi6 https://t.co/3z2wTrmcgN
Using machine learning to reduce the need for contrast agents in breast MRI through synthetic images: learn more in this editorial by Dr. Bahl of @MGHImaging. https://t.co/qDmSsykbi2 https://t.co/3iqkG6Oukl
Interesting proof of concept: Aiming to reduce Gd contrast dose by enhancing low-dose contrast breast MRI images w Generative Adversarial Networks (GAN) Probably one can work reduce Iodine contrast in contrast CT too! https://t.co/HbIJQscKYK https://t.co/FVIDbOdXr6
This will be a game changer if/when it pans out. https://t.co/aSqapchAxX https://t.co/55dlVcb5rt
Interview discussing how machine learning can generate synthetic contrast images in breast MRI, reducing the need for contrast agents, with insights from Dr. Daniel Truhn.
Interview discusses a study on using neural networks to generate synthetic breast MRI images, potentially minimizing contrast agent use. Daniel Truhn shares insights on the technology and future applications.
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This proof of concept study using Machine Learning to Reduce the Need for Contrast Agents in Breast MRI through Synthetic Images offers tremendous promise for Breast MRI. https://t.co/AJO6zIu59b
Using Machine Learning to Reduce the Need for Contrast Agents in Breast MRI through Synthetic Images https://t.co/lCcOIj5YM5 https://t.co/vUWIK5Vu6E
Using Machine Learning to Reduce the Need for Contrast Agents in Breast MRI through Synthetic Images. Gustav Müller-Franzes https://t.co/CFyUSR3mjE https://t.co/Tl3YGlpWNg
RT @radiology_rsna: Using machine learning to reduce the need for contrast agents in breast MRI through synthetic images: learn more in th…
This will be a game changer if/when it pans out. https://t.co/aSqapchAxX https://t.co/55dlVcb5rt
Using machine learning to reduce the need for contrast agents in breast MRI through synthetic images: learn more in this editorial by Dr. Bahl of @MGHImaging. https://t.co/qDmSsykbi2 https://t.co/3iqkG6Oukl
RT @radiology_rsna: Using a training set of standardized contrast-enhanced breast MRI scans, GANs recovered image appearance and conspicuit…
RT @radiology_rsna: Using a training set of standardized contrast-enhanced breast MRI scans, GANs recovered image appearance and conspicuit…
RT @DrLindaMoy: #RADIOLOGY AI generated low dose breast MRI https://t.co/d0u2ilQsYR @radiology_rsna @ProfKuhl #breastradiology #breastmri…
Using a training set of standardized contrast-enhanced breast MRI scans, GANs recovered image appearance and conspicuity of enhancing lesions from simulated low-contrast images, as verified on independent test sets. https://t.co/2hPbOHPNi6 https://t.co/3z2wTrmcgN
Using Machine Learning to Reduce the Need for Contrast Agents in Breast MRI through Synthetic Images | Radiology https://t.co/4RvuzSbtGW
RT @DrLindaMoy: #RADIOLOGY AI generated low dose breast MRI https://t.co/d0u2ilQsYR @radiology_rsna @ProfKuhl #breastradiology #breastmri…
#RADIOLOGY AI generated low dose breast MRI https://t.co/d0u2ilQsYR @radiology_rsna @ProfKuhl #breastradiology #breastmri #mri https://t.co/HpDUgrFGBy
Interesting proof of concept: Aiming to reduce Gd contrast dose by enhancing low-dose contrast breast MRI images w Generative Adversarial Networks (GAN) Probably one can work reduce Iodine contrast in contrast CT too! https://t.co/HbIJQscKYK https://t.co/FVIDbOdXr6
Using Machine Learning to Reduce the Need for Contrast Agents in Breast MRI through Synthetic Images https://t.co/oMTuursIM9
Using Machine Learning to Reduce the Need for Contrast Agents in Breast MRI through Synthetic Images by Gustav Müller-Franzes https://t.co/CASm6osJiT
Using Machine Learning to Reduce the Need for Contrast Agents in ... - RSNA Publications Online https://t.co/ZibUUBiXev