130 citations · 260 across the 13 of their papers we have counts for
15 papers · 1 filter
Super Characters: A Conversion from Sentiment Classification to Image Classification
Baohua Sun, Lin Yang, Patrick Dong +3
We propose a method named Super Characters for sentiment classification. This method converts the sentiment classification problem into image classification problem by projecting t…
CT Image Enhancement Using Stacked Generative Adversarial Networks and Transfer Learning for Lesion Segmentation Improvement
Youbao Tang, Jinzheng Cai, Le Lu +5
Automated lesion segmentation from computed tomography (CT) is an important and challenging task in medical image analysis. While many advancements have been made, there is room fo…
Iterative Attention Mining for Weakly Supervised Thoracic Disease Pattern Localization in Chest X-Rays
Jinzheng Cai, Le Lu, Adam P. Harrison +3
Given image labels as the only supervisory signal, we focus on harvesting, or mining, thoracic disease localizations from chest X-ray images. Harvesting such localizations from exi…
Accurate Weakly-Supervised Deep Lesion Segmentation using Large-Scale Clinical Annotations: Slice-Propagated 3D Mask Generation from 2D RECIST
Jinzheng Cai, Youbao Tang, Le Lu +5
Volumetric lesion segmentation from computed tomography (CT) images is a powerful means to precisely assess multiple time-point lesion/tumor changes. However, because manual 3D seg…
Deep Learning Based Instance Segmentation in 3D Biomedical Images Using Weak Annotation
Zhuo Zhao, Lin Yang, Hao Zheng +3
Instance segmentation in 3D images is a fundamental task in biomedical image analysis. While deep learning models often work well for 2D instance segmentation, 3D instance segmenta…
BoxNet: Deep Learning Based Biomedical Image Segmentation Using Boxes Only Annotation
Lin Yang, Yizhe Zhang, Zhuo Zhao +5
In recent years, deep learning (DL) methods have become powerful tools for biomedical image segmentation. However, high annotation efforts and costs are commonly needed to acquire…