activity
20172026
most citedSynSeg-Net: Synthetic Segmentation Without Target Modality Ground Truth

239 citations · 963 across the 124 of their papers we have counts for

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Showing 2018Show all

8 papers · 1 filter

cs.IR2018

Montage based 3D Medical Image Retrieval from Traumatic Brain Injury Cohort using Deep Convolutional Neural Network

Cailey I. Kerley, Yuankai Huo, Shikha Chaganti +3

Brain imaging analysis on clinically acquired computed tomography (CT) is essential for the diagnosis, risk prediction of progression, and treatment of the structural phenotypes of…

cs.CV2018

Towards Machine Learning Prediction of Deep Brain Stimulation (DBS) Intra-operative Efficacy Maps

Camilo Bermudez, William Rodriguez, Yuankai Huo +7

Deep brain stimulation (DBS) has the potential to improve the quality of life of people with a variety of neurological diseases. A key challenge in DBS is in the placement of a sti…

cs.CV2018★ 1 cited

Coronary Calcium Detection using 3D Attention Identical Dual Deep Network Based on Weakly Supervised Learning

Yuankai Huo, James G. Terry, Jiachen Wang +6

Coronary artery calcium (CAC) is biomarker of advanced subclinical coronary artery disease and predicts myocardial infarction and death prior to age 60 years. The slice-wise manual…

cs.CV2018

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…

cs.CV2018★ 239 cited

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…

cs.LG2018

Data-driven Probabilistic Atlases Capture Whole-brain Individual Variation

Yuankai Huo, Katherine Swett, Susan M. Resnick +2

Probabilistic atlases provide essential spatial contextual information for image interpretation, Bayesian modeling, and algorithmic processing. Such atlases are typically construct…

cs.CV2018★ 8 cited

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)…

cs.CV2018★ 7 cited

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…