93 citations · 512 across the 21 of their papers we have counts for
22 papers
Reconstruction-Aware Cryo-EM Particle Picking
Riku Itsuji, Yuanhao Wang, Xingjian Li +3
Cryo-electron microscopy (cryo-EM) determines the structures of proteins and macromolecular assemblies at near-atomic resolution, and the final 3D reconstruction depends on extract…
SHREC 2021: Classification in cryo-electron tomograms
Ilja Gubins, Marten L. Chaillet, Gijs van der Schot +20
Cryo-electron tomography (cryo-ET) is an imaging technique that allows three-dimensional visualization of macro-molecular assemblies under near-native conditions. Cryo-ET comes wit…
Cryo-shift: Reducing domain shift in cryo-electron subtomograms with unsupervised domain adaptation and randomization
Hmrishav Bandyopadhyay, Zihao Deng, Leiting Ding +5
Cryo-Electron Tomography (cryo-ET) is a 3D imaging technology that enables the visualization of subcellular structures in situ at near-atomic resolution. Cellular cryo-ET images he…
Disentangling semantic features of macromolecules in Cryo-Electron Tomography
Kai Yi, Jianye Pang, Yungeng Zhang +2
Cryo-electron tomography (Cryo-ET) is a 3D imaging technique that enables the systemic study of shape, abundance, and distribution of macromolecular structures in single cells in n…
Active Learning to Classify Macromolecular Structures in situ for Less Supervision in Cryo-Electron Tomography
Xuefeng Du, Haohan Wang, Zhenxi Zhu +4
Motivation: Cryo-Electron Tomography (cryo-ET) is a 3D bioimaging tool that visualizes the structural and spatial organization of macromolecules at a near-native state in single ce…
Few shot domain adaptation for in situ macromolecule structural classification in cryo-electron tomograms
Liangyong Yu, Ran Li, Xiangrui Zeng +5
Motivation: Cryo-Electron Tomography (cryo-ET) visualizes structure and spatial organization of macromolecules and their interactions with other subcellular components inside singl…
Improving Lesion Segmentation for Diabetic Retinopathy using Adversarial Learning
Qiqi Xiao, Jiaxu Zou, Muqiao Yang +5
Diabetic Retinopathy (DR) is a leading cause of blindness in working age adults. DR lesions can be challenging to identify in fundus images, and automatic DR detection systems can…
AITom: Open-source AI platform for cryo-electron tomography data analysis
Xiangrui Zeng, Min Xu
Cryo-electron tomography (cryo-ET) is an emerging technology for the 3D visualization of structural organizations and interactions of subcellular components at near-native state an…
Deep Learning-Based Strategy for Macromolecules Classification with Imbalanced Data from Cellular Electron Cryotomography
Ziqian Luo, Xiangrui Zeng, Zhipeng Bao +1
Deep learning model trained by imbalanced data may not work satisfactorily since it could be determined by major classes and thus may ignore the classes with small amount of data.…
Respond-CAM: Analyzing Deep Models for 3D Imaging Data by Visualizations
Guannan Zhao, Bo Zhou, Kaiwen Wang +2
The convolutional neural network (CNN) has become a powerful tool for various biomedical image analysis tasks, but there is a lack of visual explanation for the machinery of CNNs.…
Multi-task Learning for Macromolecule Classification, Segmentation and Coarse Structural Recovery in Cryo-Tomography
Chang Liu, Xiangrui Zeng, Kaiwen Wang +2
Cellular Electron Cryo-Tomography (CECT) is a powerful 3D imaging tool for studying the native structure and organization of macromolecules inside single cells. For systematic reco…
An integration of fast alignment and maximum-likelihood methods for electron subtomogram averaging and classification
Yixiu Zhao, Xiangrui Zeng, Qiang Guo +1
Motivation: Cellular Electron CryoTomography (CECT) is an emerging 3D imaging technique that visualizes subcellular organization of single cells at submolecular resolution and in n…
Deep learning based supervised semantic segmentation of Electron Cryo-Subtomograms
Chang Liu, Xiangrui Zeng, Ruogu Lin +4
Cellular Electron Cryo-Tomography (CECT) is a powerful imaging technique for the 3D visualization of cellular structure and organization at submolecular resolution. It enables anal…
Model compression for faster structural separation of macromolecules captured by Cellular Electron Cryo-Tomography
Jialiang Guo, Bo Zhou, Xiangrui Zeng +2
Electron Cryo-Tomography (ECT) enables 3D visualization of macromolecule structure inside single cells. Macromolecule classification approaches based on convolutional neural networ…
Feature Decomposition Based Saliency Detection in Electron Cryo-Tomograms
Bo Zhou, Qiang Guo, Xiangrui Zeng +1
Electron Cryo-Tomography (ECT) allows 3D visualization of subcellular structures at the submolecular resolution in close to the native state. However, due to the high degree of str…
Improved deep learning based macromolecules structure classification from electron cryo tomograms
Chengqian Che, Ruogu Lin, Xiangrui Zeng +3
Cellular processes are governed by macromolecular complexes inside the cell. Study of the native structures of macromolecular complexes has been extremely difficult due to lack of…
A convolutional autoencoder approach for mining features in cellular electron cryo-tomograms and weakly supervised coarse segmentation
Xiangrui Zeng, Miguel Ricardo Leung, Tzviya Zeev-Ben-Mordehai +1
Cellular electron cryo-tomography enables the 3D visualization of cellular organization in the near-native state and at submolecular resolution. However, the contents of cellular t…
Deep learning based subdivision approach for large scale macromolecules structure recovery from electron cryo tomograms
Min Xu, Xiaoqi Chai, Hariank Muthakana +4
Motivation: Cellular Electron CryoTomography (CECT) enables 3D visualization of cellular organization at near-native state and in sub-molecular resolution, making it a powerful too…
De novo visual proteomics in single cells through pattern mining
Min Xu, Elitza I Tocheva, Yi-Wei Chang +2
Cryo-electron tomography enables 3D visualization of cells in a near native state at molecular resolution. The produced cellular tomograms contain detailed information about all ma…
Efficient Active Algorithms for Hierarchical Clustering
Akshay Krishnamurthy, Sivaraman Balakrishnan, Min Xu +1
Advances in sensing technologies and the growth of the internet have resulted in an explosion in the size of modern datasets, while storage and processing power continue to lag beh…
High-dimensional covariance estimation based on Gaussian graphical models
Shuheng Zhou, Philipp Rutimann, Min Xu +1
Undirected graphs are often used to describe high dimensional distributions. Under sparsity conditions, the graph can be estimated using -penalization methods. We propose a…
Forest Density Estimation
Han Liu, Min Xu, Haijie Gu +3
We study graph estimation and density estimation in high dimensions, using a family of density estimators based on forest structured undirected graphical models. For density estima…