Two papers got awarded by RSNA 2024
Our two papers referenced below received the highest honor, Magna Cum Laude Award and the prestigious Cum Laude Award at RSNA 2024!
RSNA is a top conference in the clinical field of medical imaging with a very narrow acceptance rate of about 25% and attracts top radiologists and medical imaging researchers from all over the world.
At this year’s RSNA, there were 1,312 poster presentations that passed through that narrow gate, 6 for Magna Cum Laude (0.46% chance of winning) and 19 for Cum Laude (1.45% chance of winning).
It is extremely rare and invaluable to medical imaging researchers like us to win the highest award of the conference, the Magna Cum Laude Award or the Cum Laude Award that is the second highest award at the prestigious RSNA conference.
Prof. Suzuki commented:
“I participated in and presenting at the RSNA in the past 24 years, but the Magna Cum Laude Award and Cum Laude Award were given to clinical research presented by radiologists, and I have merely seen that research by medical imaging researchers received these awards. Moreover, I don’t recall that master students have won either of these awards; and thus, I am certain that those are great accomplishments. I would like to send my highest compliments to these students of mine.”
- Magna Cum Laude
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Qu T., Yang Y., Jin Z., and Suzuki K.: Annotation-free AI learning of lung nodule segmentation in CT using weakly-supervised Massive -training Artificial neural networks
- Cum Laude
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Kodera S., Chavoshian S. M., Jin Z., Watadani T., Abe O., and Suzuki K.: Super-efficient AI for lung nodule classification in CT based on small-data massive-training artificial neural network (MTANN)
