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07/27/2023
Text-guided Foundation Model Adaptation for Pathological Image Classification
The recent surge of foundation models in computer vision and natural lan...
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06/25/2023
Exploring Data Redundancy in Real-world Image Classification through Data Selection
Deep learning models often require large amounts of data for training, l...
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11/15/2021
T-AutoML: Automated Machine Learning for Lesion Segmentation using Transformers in 3D Medical Imaging
Lesion segmentation in medical imaging has been an important topic in cl...
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10/06/2021
Improving Pneumonia Localization via Cross-Attention on Medical Images and Reports
Localization and characterization of diseases like pneumonia are primary...
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07/16/2021
Federated Whole Prostate Segmentation in MRI with Personalized Neural Architectures
Building robust deep learning-based models requires diverse training dat...
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03/30/2021
Self-supervised Image-text Pre-training With Mixed Data In Chest X-rays
Pre-trained models, e.g., from ImageNet, have proven to be effective in ...
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11/28/2020
Transformer Query-Target Knowledge Discovery (TEND): Drug Discovery from CORD-19
Previous work established skip-gram word2vec models could be used to min...
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11/23/2020
Federated Semi-Supervised Learning for COVID Region Segmentation in Chest CT using Multi-National Data from China, Italy, Japan
The recent outbreak of COVID-19 has led to urgent needs for reliable dia...
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09/25/2020
Going to Extremes: Weakly Supervised Medical Image Segmentation
Medical image annotation is a major hurdle for developing precise and ro...
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09/22/2020
Learning Image Labels On-the-fly for Training Robust Classification Models
Current deep learning paradigms largely benefit from the tremendous amou...
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07/31/2020
Weakly supervised one-stage vision and language disease detection using large scale pneumonia and pneumothorax studies
Detecting clinically relevant objects in medical images is a challenge d...
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07/10/2020
Multi-Domain Image Completion for Random Missing Input Data
Multi-domain data are widely leveraged in vision applications taking adv...
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05/29/2020
Enhancing Foreground Boundaries for Medical Image Segmentation
Object segmentation plays an important role in the modern medical image ...
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02/19/2020
When Radiology Report Generation Meets Knowledge Graph
Automatic radiology report generation has been an attracting research pr...
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10/02/2019
Weakly supervised segmentation from extreme points
Annotation of medical images has been a major bottleneck for the develop...
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07/08/2019
Correlation via synthesis: end-to-end nodule image generation and radiogenomic map learning based on generative adversarial network
Radiogenomic map linking image features and gene expression profiles is ...
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06/07/2019
When Unseen Domain Generalization is Unnecessary? Rethinking Data Augmentation
Recent advances in deep learning for medical image segmentation demonstr...
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07/19/2018
Attention-Guided Curriculum Learning for Weakly Supervised Classification and Localization of Thoracic Diseases on Chest Radiographs
In this work, we exploit the task of joint classification and weakly sup...
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01/12/2018
TieNet: Text-Image Embedding Network for Common Thorax Disease Classification and Reporting in Chest X-rays
Chest X-rays are one of the most common radiological examinations in dai...
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12/16/2017
NegBio: a high-performance tool for negation and uncertainty detection in radiology reports
Negative and uncertain medical findings are frequent in radiology report...
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11/28/2017
Deep Lesion Graphs in the Wild: Relationship Learning and Organization of Significant Radiology Image Findings in a Diverse Large-scale Lesion Database
Radiologists in their daily work routinely find and annotate significant...
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10/04/2017
DeepLesion: Automated Deep Mining, Categorization and Detection of Significant Radiology Image Findings using Large-Scale Clinical Lesion Annotations
Extracting, harvesting and building large-scale annotated radiological i...
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05/05/2017
ChestX-ray8: Hospital-scale Chest X-ray Database and Benchmarks on Weakly-Supervised Classification and Localization of Common Thorax Diseases
The chest X-ray is one of the most commonly accessible radiological exam...
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01/23/2017
Unsupervised Joint Mining of Deep Features and Image Labels for Large-scale Radiology Image Categorization and Scene Recognition
The recent rapid and tremendous success of deep convolutional neural net...
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03/25/2016