This year’s MICCAI conference had record-breaking attendance. If you missed it, view this SlideShare to catch up on all the highlights and NVIDIA news.

1. Key Takeaways from MICCAI 2018
CELEBRATING AND SUPPORTING THE
MEDICAL IMAGING COMMUNITY

2. INTERNATIONAL CONFERENCE ON
MEDICAL IMAGE COMPUTING & COMPUTER
ASSISTED INTERVENTION (MICCAI)
The 21st
MICCAI annual conference was held in Granada from
September 16th to 20th and brought together leading
biomedical scientists, engineers, and clinicians from a wide
range of disciplines.

3. MICCAI: BY THE NUMBERS
1,400+ Registered Delegates: 33% Increase over 2017
1600+ Attendees over the 2-day Satellite Events
1000+ Papers Submitted
373 Accepted Papers: 70% Feature AI
79 Posters
40 Workshops
14 Tutorials
12 Challenges
4 Keynote Speakers

4. Now in its 21st year, MICCAI is the preeminent
conference on medical imaging research,
bringing together a wide range of experts
from academia to industry and healthcare
organizations.
NVIDIA was a dedicated and active participant
at MICCAI with hosted workshops, engaging
talks, and a number of accepted papers and
posters.
MICCAI 2018
LEARN MORE ABOUT MICCAI
Source: https://blogs.nvidia.com/blog/2018/09/17/medical-imaging-deep-learning-miccai/

5. CELEBRATING RESEARCH
MICCAI 2018 boasted a robust scientific
program. With over 1,000 papers submitted,
the 373 accepted papers represented the best
of the best. NVIDIA had a dozen accepted
papers, and 6 poster presentations.
Among the research presented, the team used
an AI technique called generative adversarial
networks (GANs) to generate synthetic images
which can be used to train AI-based medical
imaging systems.
Source: https://youtu.be/BMuFk2PjEuM
WATCH NOW

6. NVIDIA DEEP LEARNING INSTITUTE (DLI)
NVIDIA hosted 200 attendees for our workshop
“Deep Learning for Healthcare Image Analysis.”
The two-part workshop featured hands-on,
instructor led training that focused on healthcare
applications including generative networks for
medical imaging and coarse to fine contextual
memory for medical imaging.
Source: https://www.nvidia.com/en-us/deep-learning-ai/education/
LEARN MORE ABOUT DLI

7. SPONSORED PAPERS AND CHALLENGES
At this year’s MICCAI Conference, NVIDIA
sponsored several papers and challenge,
including:
1st Workshop on PRedictive Intelligence in
MEdicine (PRIME-MICCAI)
Statistical Atlases and Computational Modelling of
the Heart Workshop (STATCOM)
Deep Learning in Medical Image Analysis (DLMIA)
Multi-shell Diffusion MRI Harmonisation Challenge
(MUSHAC)
Medical Segmentation Decathlon (MSD)
Source: ttps://www.miccai2018.org/en/WORKSHOP---CHALLENGE---TUTORIAL.html
LEARN MORE

8. PRIME-MICCAI CHALLENGE WINNER
"Generation of Amyloid PET Images via Conditional
Adversarial Training for Predicting Progression to
Alzheimer’s Disease”
Yu Yan, Hoileong Lee, Edward Somer,
Vicente Grau
Their paper highlights an application of conditional
generative adversarial networks to the generation
of florbetapir PET images from corresponding MRI
images.
Source: http://basira-lab.com/events-workshops/PRIME-MICCAI18/
READ MORE

9. DLMIA BEST PAPER WINNER
“Automatic Segmentation of Pulmonary Lobes Using
a Progressive Dense V-Network”
Abdullah-Al-Zubaer Irman, Ali Hatamizadeh,
Shilpa Pundi Ananth, Xuaiwei Ding, Demetri
Terzopoulos, Nima Tajbakhsh
Using one NVIDIA Titan XP GPU, their demonstrated
method can segment lung lobes in one forward pass of
the network, with an average run time of 2 seconds.
Source: https://cs.adelaide.edu.au/~dlmia4/
LEARN MORE ABOUT DLMIA

10. MEDICAL SEGMENTATION DECATHLON
The MSD challenge tests the generalizability of machine
learning algorithms when applied to 10 different
semantic segmentation tasks. The aim is to develop an
algorithm or learning system that can solve each task,
separately, without human interaction.
Source: http://medicaldecathlon.com/
READ MORE
Winner: Fabian Isensee, German Cancer
Research Center (DKFZ), Team nnU-Net (Phase
1 and 2)
1st Runner-Up: Yingda Xia, Johns Hopkins
University/NVIDIA, Team NVDLMED
2nd Runner-Up BeomHee Park, Asan Medical
Center, Team beomheep

11. BRATS CHALLENGE WINNER
BraTS (Multimodal Brain Tumor Segmentation) has
always been focused on the evaluation of
state-of-the-art methods for the segmentation of brain
tumors in multimodal magnetic resonance imaging
(MRI) scans.
This year, NVIDIA’s own Andriy Myronenko, Lead
Scientist of Brain Segmentation, won first place in the
challenge from 390 participants.
Source: https://www.cbica.upenn.edu/sbia/Spyridon.Bakas/MICCAI_BraTS/MICCAI_BraTS_2018_proceedings_shortPapers.pdf
LEARN MORE

12. THE YOUNG SCIENTIST IMPACT AWARD
The MICCAI Young Scientist Impact Award
recognizes those who have had a significant
impact in their field so early in their career.
This year, NVIDIA’s Dr. Holger Roth won the
Young Scientist Impact Award for pioneering
deep learning in medical imaging.
VIEW RECENT WORK
Source: http://www.cs.jhu.edu/~lelu/publication/MICCAI2018_Colonoscopy.pdf

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14. To learn more about NVIDIA in
healthcare, visit:
http://www.nvidia.com/healthcare