3.1k citations · 7.6k across the 74 of their papers we have counts for
11 papers · 1 filter
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…
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…
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…
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…
Inter-Scanner Harmonization of High Angular Resolution DW-MRI using Null Space Deep Learning
Vishwesh Nath, Prasanna Parvathaneni, Colin B. Hansen +15
Diffusion-weighted magnetic resonance imaging (DW-MRI) allows for non-invasive imaging of the local fiber architecture of the human brain at a millimetric scale. Multiple classical…
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…
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…
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…
Why rankings of biomedical image analysis competitions should be interpreted with care
Lena Maier-Hein, Matthias Eisenmann, Annika Reinke +35
International challenges have become the standard for validation of biomedical image analysis methods. Given their scientific impact, it is surprising that a critical analysis of c…
Learning Implicit Brain MRI Manifolds with Deep Learning
Camilo Bermudez, Andrew J. Plassard, Larry T. Davis +3
An important task in image processing and neuroimaging is to extract quantitative information from the acquired images in order to make observations about the presence of disease o…