research
∙
08/06/2023
Early Detection and Localization of Pancreatic Cancer by Label-Free Tumor Synthesis
Early detection and localization of pancreatic cancer can increase the 5...
share
research
∙
06/01/2023
Continual Learning for Abdominal Multi-Organ and Tumor Segmentation
The ability to dynamically extend a model to new data and classes is cri...
research
∙
05/16/2023
Annotating 8,000 Abdominal CT Volumes for Multi-Organ Segmentation in Three Weeks
Annotating medical images, particularly for organ segmentation, is labor...
research
∙
04/04/2023
TPU v4: An Optically Reconfigurable Supercomputer for Machine Learning with Hardware Support for Embeddings
In response to innovations in machine learning (ML) models, production w...
research
∙
03/27/2023
Label-Free Liver Tumor Segmentation
We demonstrate that AI models can accurately segment liver tumors withou...
research
∙
01/02/2023
CLIP-Driven Universal Model for Organ Segmentation and Tumor Detection
An increasing number of public datasets have shown a marked clinical imp...
research
∙
10/26/2022
Synthetic Tumors Make AI Segment Tumors Better
We develop a novel strategy to generate synthetic tumors. Unlike existin...
research
∙
10/23/2022
Delving into Masked Autoencoders for Multi-Label Thorax Disease Classification
Vision Transformer (ViT) has become one of the most popular neural archi...
research
∙
10/05/2022
Making Your First Choice: To Address Cold Start Problem in Vision Active Learning
Active learning promises to improve annotation efficiency by iteratively...
research
∙
07/06/2022
Unsupervised Domain Adaptation through Shape Modeling for Medical Image Segmentation
Shape information is a strong and valuable prior in segmenting organs in...
research
∙
04/05/2022
PaLM: Scaling Language Modeling with Pathways
Large language models have been shown to achieve remarkable performance ...
research
∙
12/13/2021
GLaM: Efficient Scaling of Language Models with Mixture-of-Experts
Scaling language models with more data, compute and parameters has drive...
research
∙
12/03/2021
MT-TransUNet: Mediating Multi-Task Tokens in Transformers for Skin Lesion Segmentation and Classification
Recent advances in automated skin cancer diagnosis have yielded performa...
research
∙
11/26/2021
In-painting Radiography Images for Unsupervised Anomaly Detection
We propose space-aware memory queues for in-painting and detecting anoma...
research
∙
11/25/2021
Learning from Temporal Gradient for Semi-supervised Action Recognition
Semi-supervised video action recognition tends to enable deep neural net...
research
∙
09/27/2021
BigSSL: Exploring the Frontier of Large-Scale Semi-Supervised Learning for Automatic Speech Recognition
We summarize the results of a host of efforts using giant automatic spee...
research
∙
09/25/2021
Data, Assemble: Leveraging Multiple Datasets with Heterogeneous and Partial Labels
The success of deep learning relies heavily on large datasets with exten...
research
∙
09/15/2021
Seeking an Optimal Approach for Computer-Aided Pulmonary Embolism Detection
Pulmonary embolism (PE) represents a thrombus ("blood clot"), usually or...
research
∙
02/21/2021
Transferable Visual Words: Exploiting the Semantics of Anatomical Patterns for Self-supervised Learning
This paper introduces a new concept called "transferable visual words" (...
research
∙
07/14/2020
Learning Semantics-enriched Representation via Self-discovery, Self-classification, and Self-restoration
Medical images are naturally associated with rich semantics about the hu...
research
∙
12/11/2019
UNet++: Redesigning Skip Connections to Exploit Multiscale Features in Image Segmentation
The state-of-the-art models for medical image segmentation are variants ...
research
∙
09/21/2019
Scale MLPerf-0.6 models on Google TPU-v3 Pods
The recent submission of Google TPU-v3 Pods to the industry wide MLPerf ...
research
∙
08/19/2019
Models Genesis: Generic Autodidactic Models for 3D Medical Image Analysis
Transfer learning from natural image to medical image has established as...
research
∙
08/16/2019
Learning Fixed Points in Generative Adversarial Networks: From Image-to-Image Translation to Disease Detection and Localization
Generative adversarial networks (GANs) have ushered in a revolution in i...
research
∙
07/18/2018
UNet++: A Nested U-Net Architecture for Medical Image Segmentation
In this paper, we present UNet++, a new, more powerful architecture for ...
research
∙
02/03/2018
AFT*: Integrating Active Learning and Transfer Learning to Reduce Annotation Efforts
The splendid success of convolutional neural networks (CNNs) in computer...
research
∙
02/07/2017