239 citations · 513 across the 18 of their papers we have counts for
14 papers · 1 filter
COLosSAL: A Benchmark for Cold-start Active Learning for 3D Medical Image Segmentation
Han Liu, Hao Li, Xing Yao +6
Medical image segmentation is a critical task in medical image analysis. In recent years, deep learning based approaches have shown exceptional performance when trained on a fully-…
COSST: Multi-organ Segmentation with Partially Labeled Datasets Using Comprehensive Supervisions and Self-training
Han Liu, Zhoubing Xu, Riqiang Gao +5
Deep learning models have demonstrated remarkable success in multi-organ segmentation but typically require large-scale datasets with all organs of interest annotated. However, med…
A Comparative Study of Confidence Calibration in Deep Learning: From Computer Vision to Medical Imaging
Riqiang Gao, Thomas Li, Yucheng Tang +7
Although deep learning prediction models have been successful in the discrimination of different classes, they can often suffer from poor calibration across challenging domains inc…
3D Whole Brain Segmentation using Spatially Localized Atlas Network Tiles
Yuankai Huo, Zhoubing Xu, Yunxi Xiong +7
Detailed whole brain segmentation is an essential quantitative technique, which provides a non-invasive way of measuring brain regions from a structural magnetic resonance imaging…
Class-Aware Adversarial Lung Nodule Synthesis in CT Images
Jie Yang, Siqi Liu, Sasa Grbic +7
Though large-scale datasets are essential for training deep learning systems, it is expensive to scale up the collection of medical imaging datasets. Synthesizing the objects of in…
Decompose to manipulate: Manipulable Object Synthesis in 3D Medical Images with Structured Image Decomposition
Siqi Liu, Eli Gibson, Sasa Grbic +5
The performance of medical image analysis systems is constrained by the quantity of high-quality image annotations. Such systems require data to be annotated by experts with years…
Splenomegaly Segmentation on Multi-modal MRI using Deep Convolutional Networks
Yuankai Huo, Zhoubing Xu, Shunxing Bao +8
The findings of splenomegaly, abnormal enlargement of the spleen, is a non-invasive clinical biomarker for liver and spleen disease. Automated segmentation methods are essential to…
SynSeg-Net: Synthetic Segmentation Without Target Modality Ground Truth
Yuankai Huo, Zhoubing Xu, Hyeonsoo Moon +6
A key limitation of deep convolutional neural networks (DCNN) based image segmentation methods is the lack of generalizability. Manually traced training images are typically requir…
Spatially Localized Atlas Network Tiles Enables 3D Whole Brain Segmentation from Limited Data
Yuankai Huo, Zhoubing Xu, Katherine Aboud +6
Whole brain segmentation on a structural magnetic resonance imaging (MRI) is essential in non-invasive investigation for neuroanatomy. Historically, multi-atlas segmentation (MAS)…
Less is More: Simultaneous View Classification and Landmark Detection for Abdominal Ultrasound Images
Zhoubing Xu, Yuankai Huo, JinHyeong Park +4
An abdominal ultrasound examination, which is the most common ultrasound examination, requires substantial manual efforts to acquire standard abdominal organ views, annotate the vi…
Select, Attend, and Transfer: Light, Learnable Skip Connections
Saeid Asgari Taghanaki, Aicha Bentaieb, Anmol Sharma +8
Skip connections in deep networks have improved both segmentation and classification performance by facilitating the training of deeper network architectures, and reducing the risk…
Adversarial Synthesis Learning Enables Segmentation Without Target Modality Ground Truth
Yuankai Huo, Zhoubing Xu, Shunxing Bao +3
A lack of generalizability is one key limitation of deep learning based segmentation. Typically, one manually labels new training images when segmenting organs in different imaging…
Splenomegaly Segmentation using Global Convolutional Kernels and Conditional Generative Adversarial Networks
Yuankai Huo, Zhoubing Xu, Shunxing Bao +7
Spleen volume estimation using automated image segmentation technique may be used to detect splenomegaly (abnormally enlarged spleen) on Magnetic Resonance Imaging (MRI) scans. In…
Automatic Vertebra Labeling in Large-Scale 3D CT using Deep Image-to-Image Network with Message Passing and Sparsity Regularization
Dong Yang, Tao Xiong, Daguang Xu +10
Automatic localization and labeling of vertebra in 3D medical images plays an important role in many clinical tasks, including pathological diagnosis, surgical planning and postope…