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20192024
most citedDistanced LSTM: Time-Distanced Gates in Long Short-Term Memory Models for Lung Cancer Detection

7 citations · 40 across the 24 of their papers we have counts for

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16 papers · 1 filter

eess.IV2023

Deep conditional generative models for longitudinal single-slice abdominal computed tomography harmonization

Xin Yu, Qi Yang, Yucheng Tang +8

Two-dimensional single-slice abdominal computed tomography (CT) provides a detailed tissue map with high resolution allowing quantitative characterization of relationships between…

eess.IV2023

Longitudinal Multimodal Transformer Integrating Imaging and Latent Clinical Signatures From Routine EHRs for Pulmonary Nodule Classification

Thomas Z. Li, John M. Still, Kaiwen Xu +11

The accuracy of predictive models for solitary pulmonary nodule (SPN) diagnosis can be greatly increased by incorporating repeat imaging and medical context, such as electronic hea…

eess.IV2022★ 4 cited

Reducing Positional Variance in Cross-sectional Abdominal CT Slices with Deep Conditional Generative Models

Xin Yu, Qi Yang, Yucheng Tang +8

2D low-dose single-slice abdominal computed tomography (CT) slice enables direct measurements of body composition, which are critical to quantitatively characterizing health relati…

eess.IV2022★ 1 cited

Time-distance vision transformers in lung cancer diagnosis from longitudinal computed tomography

Thomas Z. Li, Kaiwen Xu, Riqiang Gao +5

Features learned from single radiologic images are unable to provide information about whether and how much a lesion may be changing over time. Time-dependent features computed fro…

eess.IV2022★ 4 cited

UNesT: Local Spatial Representation Learning with Hierarchical Transformer for Efficient Medical Segmentation

Xin Yu, Qi Yang, Yinchi Zhou +12

Transformer-based models, capable of learning better global dependencies, have recently demonstrated exceptional representation learning capabilities in computer vision and medical…

eess.IV2022★ 1 cited

Body Composition Assessment with Limited Field-of-view Computed Tomography: A Semantic Image Extension Perspective

Kaiwen Xu, Thomas Li, Mirza S. Khan +6

Field-of-view (FOV) tissue truncation beyond the lungs is common in routine lung screening computed tomography (CT). This poses limitations for opportunistic CT- based body composi…

eess.IV2022★ 4 cited

Pseudo-Label Guided Multi-Contrast Generalization for Non-Contrast Organ-Aware Segmentation

Ho Hin Lee, Yucheng Tang, Riqiang Gao +7

Non-contrast computed tomography (NCCT) is commonly acquired for lung cancer screening, assessment of general abdominal pain or suspected renal stones, trauma evaluation, and many…

eess.IV2022★ 4 cited

Characterizing Renal Structures with 3D Block Aggregate Transformers

Xin Yu, Yucheng Tang, Yinchi Zhou +10

Efficiently quantifying renal structures can provide distinct spatial context and facilitate biomarker discovery for kidney morphology. However, the development and evaluation of t…

eess.IV2021★ 1 cited

Random Multi-Channel Image Synthesis for Multiplexed Immunofluorescence Imaging

Shunxing Bao, Yucheng Tang, Ho Hin Lee +8

Multiplex immunofluorescence (MxIF) is an emerging imaging technique that produces the high sensitivity and specificity of single-cell mapping. With a tenet of 'seeing is believing…

eess.IV2021

Lung Cancer Risk Estimation with Incomplete Data: A Joint Missing Imputation Perspective

Riqiang Gao, Yucheng Tang, Kaiwen Xu +7

Data from multi-modality provide complementary information in clinical prediction, but missing data in clinical cohorts limits the number of subjects in multi-modal learning contex…

eess.IV2020

Development and Characterization of a Chest CT Atlas

Kaiwen Xu, Riqiang Gao, Mirza S. Khan +8

A major goal of lung cancer screening is to identify individuals with particular phenotypes that are associated with high risk of cancer. Identifying relevant phenotypes is complic…

eess.IV2020

Deep Multi-path Network Integrating Incomplete Biomarker and Chest CT Data for Evaluating Lung Cancer Risk

Riqiang Gao, Yucheng Tang, Kaiwen Xu +7

Clinical data elements (CDEs) (e.g., age, smoking history), blood markers and chest computed tomography (CT) structural features have been regarded as effective means for assessing…

eess.IV2020

Validation and Optimization of Multi-Organ Segmentation on Clinical Imaging Archives

Yuchen Xu, Olivia Tang, Yucheng Tang +9

Segmentation of abdominal computed tomography(CT) provides spatial context, morphological properties, and a framework for tissue-specific radiomics to guide quantitative Radiologic…

eess.IV2019★ 3 cited

Contrast Phase Classification with a Generative Adversarial Network

Yucheng Tang, Ho Hin Lee, Yuchen Xu +10

Dynamic contrast enhanced computed tomography (CT) is an imaging technique that provides critical information on the relationship of vascular structure and dynamics in the context…

eess.IV2019

Semi-Supervised Multi-Organ Segmentation through Quality Assurance Supervision

Ho Hin Lee, Yucheng Tang, Olivia Tang +9

Human in-the-loop quality assurance (QA) is typically performed after medical image segmentation to ensure that the systems are performing as intended, as well as identifying and e…

eess.IV2019★ 7 cited

Distanced LSTM: Time-Distanced Gates in Long Short-Term Memory Models for Lung Cancer Detection

Riqiang Gao, Yuankai Huo, Shunxing Bao +9

The field of lung nodule detection and cancer prediction has been rapidly developing with the support of large public data archives. Previous studies have largely focused on cross-…