Главная
Study mode:
on
1
Introduction
2
History of segmentation
3
Deep learning in segmentation
4
Neural Architecture Search
5
Multipath Search
6
Optimal Solutions
7
Recent Literature
8
Optimization
9
Beyond AutoML
10
Summary
11
Questions
Description:
Explore cutting-edge techniques in medical image segmentation, AutoML, and advanced topics in this comprehensive talk by NVIDIA's Applied Research Scientist, Dong Yang. Delve into the evolution of image segmentation, the impact of deep learning, and the potential of Automated Machine Learning (AutoML) in enhancing model efficiency. Discover a novel method that systematically considers multiple components of deep neural network-based solutions for 3D medical image segmentation. Examine the proposed predictor-based AutoML algorithm and its large-scale neural architecture search space. Gain insights into state-of-the-art performance on lesion segmentation datasets and the method's transferability across different datasets. Explore additional topics such as transformer-based networks, federated learning, semi-supervised learning, and the integration of shape priors in segmentation. Conclude with a summary and Q&A session to deepen your understanding of modern medical image analysis techniques. Read more

Modern Medical Image Segmentation, AutoML, and Beyond

Nvidia
Add to list
0:00 / 0:00