Localized multiscale texture based retrieval of neurological image. - Sidong Liu; Lei Jing; Weidong Cai 001; Lingfeng Wen; Stefan Eberl; Michael J. Fulham; David Dagan Feng (CBMS, 2010)

3D neurological image retrieval with localized pathology-centric CMRGlc patterns. - Weidong Cai 001; Sidong Liu; Lingfeng Wen; Stefan Eberl; Michael J. Fulham; David Dagan Feng (ICIP, 2010)

Generalized regional disorder-sensitive-weighting scheme for 3D neuroimaging retrieval. - Sidong Liu; Weidong Cai 001; Lingfeng Wen; Stefan Eberl; Michael J. Fulham; David Dagan Feng (EMBC, 2011)

Localized functional neuroimaging retrieval using 3D discrete curvelet transform. - Sidong Liu; Weidong Cai 001; Lingfeng Wen; Stefan Eberl; Michael J. Fulham; David Dagan Feng (ISBI, 2011)

Multiscale and multiorientation feature extraction with degenerative patterns for 3D neuroimaging retrieval. - Sidong Liu; Weidong Cai 001; Lingfeng Wen; David Dagan Feng (ICIP, 2012)

Localized Sparse Code Gradient in Alzheimer's disease staging. - Sidong Liu; Weidong Cai 001; Yang Song 001; Sonia Pujol; Ron Kikinis; Lingfeng Wen; David Dagan Feng (EMBC, 2013)

A supervised multiview spectral embedding method for neuroimaging classification. - Sidong Liu; Lelin Zhang; Weidong Cai 001; Yang Song 001; Zhiyong Wang 001; Lingfeng Wen; David Dagan Feng (ICIP, 2013)

Graph cuts based relevance feedback in image retrieval. - Lelin Zhang; Sidong Liu; Zhiyong Wang 001; Weidong Cai 001; Yang Song 001; David Dagan Feng (ICIP, 2013)

Multi-Channel brain atrophy pattern analysis in neuroimaging retrieval. - Sidong Liu; Weidong Cai 001; Lingfeng Wen; Dagan Feng 001 (ISBI, 2013)

Neuroimaging biomarker based prediction of Alzheimer'S disease severity with optimized graph construction. - Sidong Liu; Weidong Cai 001; Lingfeng Wen; Dagan Feng 001 (ISBI, 2013)

Multifold Bayesian Kernelization in Alzheimer's Diagnosis. - Sidong Liu; Yang Song 001; Weidong Cai 001; Sonia Pujol; Ron Kikinis; Xiaogang Wang 001; Dagan Feng 001 (MICCAI (2), 2013)

Latent Semantic Association for Medical Image Retrieval. - Fan Zhang 013; Yang Song 001; Sidong Liu; Sonia Pujol; Ron Kikinis; David Dagan Feng; Tom Weidong Cai (DICTA, 2014)

Hierarchical and binary spatial descriptors for lung nodule image retrieval. - Gillian Ng; Yang Song 001; Weidong Cai 001; Yun Zhou 006; Sidong Liu; David Dagan Feng (EMBC, 2014)

Propagation graph fusion for multi-modal medical content-based retrieval. - Sidong Liu; Siqi Liu 001; Sonia Pujol; Ron Kikinis; Dagan Feng 001; Weidong Cai 001 (ICARCV, 2014)

Automated feedback extraction for medical imaging retrieval. - Weidong Cai 001; Fan Zhang 013; Yang Song 001; Sidong Liu; Lingfeng Wen; Stefan Eberl; Michael J. Fulham; Dagan Feng 001 (ISBI, 2014)

Co-neighbor multi-view spectral embedding for medical content-based retrieval. - Hangyu Che; Sidong Liu; Weidong Cai 001; Sonia Pujol; Ron Kikinis; Dagan Feng 001 (ISBI, 2014)

Early diagnosis of Alzheimer's disease with deep learning. - Siqi Liu 001; Sidong Liu; Weidong Cai 001; Sonia Pujol; Ron Kikinis; Dagan Feng 001 (ISBI, 2014)

Multi-Channel neurodegenerative pattern analysis and its application in Alzheimer's disease characterization. - Sidong Liu; Weidong Cai 001; Lingfeng Wen; David Dagan Feng; Sonia Pujol; Ron Kikinis; Michael J. Fulham; Stefan Eberl (Comput. Medical Imaging Graph., 2014)

Multi-Phase Feature Representation Learning for Neurodegenerative Disease Diagnosis. - Siqi Liu 001; Sidong Liu; Tom Weidong Cai; Sonia Pujol; Ron Kikinis; David Dagan Feng (ACALCI, 2015)

Ranking-Based Vocabulary Pruning in Bag-of-Features for Image Retrieval. - Fan Zhang 013; Yang Song 001; Tom Weidong Cai; Alexander G. Hauptmann; Sidong Liu; Siqi Liu 001; David Dagan Feng; Mei Chen (ACALCI, 2015)

Content-Based Retrieval of Brain Diffusion Magnetic Resonance Image. - Siqi Liu 001; Nur Hadi; Sidong Liu; Sonia Pujol; Ron Kikinis; Fan Zhang 013; Dagan Feng 001; Weidong Cai 001 (MRDM@ECIR, 2015)

Subject-centered multi-view feature fusion for neuroimaging retrieval and classification. - Sidong Liu; Tom Weidong Cai; Siqi Liu 001; Sonia Pujol; Ron Kikinis; David Dagan Feng (ICIP, 2015)

Longitudinal brain MR retrieval with diffeomorphic demons registration: What happened to those patients with similar changes? - Siqi Liu 001; Sidong Liu; Fan Zhang 013; Tom Weidong Cai; Sonia Pujol; Ron Kikinis; David Dagan Feng (ISBI, 2015)

Motion Representation of Ciliated Cell Images with Contour-Alignment for Automated CBF Estimation. - Fan Zhang 013; Yang Song 001; Siqi Liu 001; Paul M. Young; Daniela Traini; Lucy Morgan; Hui-Xin Ong; Lachlan Buddle; Sidong Liu; David Dagan Feng; Tom Weidong Cai (MICCAI (3), 2015)

Multimodal neuroimaging computing: a review of the applications in neuropsychiatric disorders. - Sidong Liu; Weidong Cai 001; Siqi Liu 001; Fan Zhang 013; Michael J. Fulham; Dagan Feng 001; Sonia Pujol; Ron Kikinis (Brain Informatics, 2015)

Multimodal neuroimaging computing: the workflows, methods, and platforms. - Sidong Liu; Weidong Cai 001; Siqi Liu 001; Fan Zhang 013; Michael J. Fulham; Dagan Feng 001; Sonia Pujol; Ron Kikinis (Brain Informatics, 2015)

Morphometry-Based Longitudinal Neurodegeneration Simulation with MR Imaging. - Siqi Liu 001; Sidong Liu; Sonia Pujol; Ron Kikinis; Dagan Feng 001; Michael J. Fulham; Weidong Cai 001 (CoRR, 2015)

Multimodal Neuroimaging Feature Learning for Multiclass Diagnosis of Alzheimer's Disease. - Siqi Liu 001; Sidong Liu; Weidong Cai 001; Hangyu Che; Sonia Pujol; Ron Kikinis; Dagan Feng 001; Michael J. Fulham (IEEE Trans. Biomed. Eng., 2015)

Multimodal Neuroimaging Analysis for Neurodegeneration Characterization. - Sidong Liu (2015)

Clique Identification and Propagation for Multimodal Brain Tumor Image Segmentation. - Sidong Liu; Yang Song 001; Fan Zhang 013; Dagan Feng 001; Michael J. Fulham; Tom Weidong Cai (BIH, 2016)

Reconstruction of 3D neuron morphology using Rivulet back-tracking. - Donghao Zhang; Siqi Liu 001; Sidong Liu; Dagan Feng 001; Hanchuan Peng; Weidong Cai 001 (ISBI, 2016)

Lung Nodule Classification by Jointly Using Visual Descriptors and Deep Features. - Yutong Xie 001; Jianpeng Zhang; Sidong Liu; Weidong Cai 001; Yong Xia 001 (MCV/BAMBI@MICCAI, 2016)

Self-scheduling of a power generating company: Carbon tax considerations. - Sidong Liu; Julien Chevallier; Bangzhu Zhu (Comput. Oper. Res., 2016)

Dictionary pruning with visual word significance for medical image retrieval. - Fan Zhang 013; Yang Song 001; Weidong Cai 001; Alexander G. Hauptmann; Sidong Liu; Sonia Pujol; Ron Kikinis; Michael J. Fulham; David Dagan Feng; Mei Chen (Neurocomputing, 2016)

Rivulet: 3D Neuron Morphology Tracing with Iterative Back-Tracking. - Siqi Liu 001; Donghao Zhang; Sidong Liu; Dagan Feng 001; Hanchuan Peng; Weidong Cai 001 (Neuroinformatics, 2016)

Pairwise Latent Semantic Association for Similarity Computation in Medical Imaging. - Fan Zhang 013; Yang Song 001; Weidong Cai 001; Sidong Liu; Siqi Liu 001; Sonia Pujol; Ron Kikinis; Yong Xia 001; Michael J. Fulham; David Dagan Feng (IEEE Trans. Biomed. Eng., 2016)

Multimodal Neuroimaging Computing for the Characterization of Neurodegenerative Disorders - Sidong Liu (Springer, 2017)

MS-GAN: GAN-Based Semantic Segmentation of Multiple Sclerosis Lesions in Brain Magnetic Resonance Imaging. - Chaoyi Zhang; Yang Song 001; Sidong Liu; Scott Lill; Chenyu Wang 001; Zihao Tang; Yuyi You; Yang Gao; Alexander Klistorner; Michael Barnett 006; Weidong Cai 001 (DICTA, 2018)

Whole Slide Image Classification via Iterative Patch Labelling. - Chaoyi Zhang; Yang Song 001; Donghao Zhang; Sidong Liu; Mei Chen; Weidong Cai 001 (ICIP, 2018)

Feature learning with component selective encoding for histopathology image classification. - Yang Song 001; Hang Chang; Yang Gao; Sidong Liu; Donghao Zhang; Junen Yao; Wojciech Chrzanowski; Weidong Cai 001 (ISBI, 2018)

Automatic Segmentation of Thigh Muscle in Longitudinal 3D T1-Weighted Magnetic Resonance (MR) Images. - Zihao Tang; Chenyu Wang 001; Phu Hoang; Sidong Liu; Weidong Cai 001; Domenic Soligo; Ruth Oliver; Michael Barnett 006; Ché Fornusek (DATRA/PIPPI@MICCAI, 2018)

Filtering method of rock points based on BP neural network and principal component analysis. - Jun Xiao 005; Sidong Liu; Liang Hu; Ying Wang 030 (Frontiers Comput. Sci., 2018)

Impact of Spherical Coordinates Transformation Pre-processing in Deep Convolution Neural Networks for Brain Tumor Segmentation and Survival Prediction. - Carlo Russo; Sidong Liu; Antonio Di Ieva (BrainLes@MICCAI (1), 2020)

Voice Command Recognition Using Biologically Inspired Time-Frequency Representation and Convolutional Neural Networks. - Roneel V. Sharan; Shlomo Berkovsky; Sidong Liu (EMBC, 2020)

Robust Vision-Based Workout Analysis Using Diversified Deep Latent Variable Model. - Hao Xiong 001; Shlomo Berkovsky; Roneel V. Sharan; Sidong Liu; Enrico W. Coiera (EMBC, 2020)

Detecting Transaction-based Tax Evasion Activities on Social Media Platforms Using Multi-modal Deep Neural Networks. - Lelin Zhang; Xi Nan; Eva Huang; Sidong Liu (CoRR, 2020)

Detection of ship targets in photoelectric images based on an improved recurrent attention convolutional neural network. - Zhijing Xu; Yuhao Huo; Kun Liu 020; Sidong Liu (Int. J. Distributed Sens. Networks, 2020)

An Improved InceptionV3 Network for Obscured Ship Classification in Remote Sensing Images. - Kun Liu 020; Shengtao Yu; Sidong Liu (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2020)

Social E-commerce Tax Evasion Detection Using Multi-modal Deep Neural Networks. - Lelin Zhang; Xi Nan; Eva Huang; Sidong Liu (DICTA, 2021)

Texture Enhanced Generative Adversarial Network For Stain Normalisation In Histopathology Images. - Cong Cong; Sidong Liu; Antonio Di Ieva; Maurice Pagnucco; Shlomo Berkovsky; Yang Song 001 (ISBI, 2021)

Semi-supervised Adversarial Learning for Stain Normalisation in Histopathology Images. - Cong Cong; Sidong Liu; Antonio Di Ieva; Maurice Pagnucco; Shlomo Berkovsky; Yang Song 001 (MICCAI (8), 2021)

Severity Assessment and Progression Prediction of COVID-19 Patients Based on the LesionEncoder Framework and Chest CT. - You-Zhen Feng; Sidong Liu; Zhong-Yuan Cheng; Juan C. Quiroz; Dana Rezazadegan; Ping-Kang Chen; Qi-Ting Lin; Long Qian; Xiao-Fang Liu; Shlomo Berkovsky; Enrico W. Coiera; Lei Song; et al. (Inf., 2021)

Prediction of anxiety disorders using a feature ensemble based bayesian neural network. - Hao Xiong 001; Shlomo Berkovsky; Mia Romano; Roneel V. Sharan; Sidong Liu; Enrico W. Coiera; Lauren F. McLellan (J. Biomed. Informatics, 2021)

Integrating eye gaze into machine learning using fractal curves. - Robert Ahadizad Newport; Sidong Liu; Antonio Di Ieva (Gaze Meets ML, 2022)

Optimal and Adaptive 1553B Telemetry Scheduling for Flight Control Software Based on Dynamic Programming. - Fei Gao; Hong Huo; Huimin Ren; Sidong Liu; Zhong Yu (ICSIE, 2022)

Imbalanced Histopathology Image Classification Using Deep Feature Graph Attention Network. - Cong Cong; Yixing Yang; Sidong Liu; Maurice Pagnucco; Yang Song 001 (ISBI, 2022)

Adaptive Unified Contrastive Learning for Imbalanced Classification. - Cong Cong; Yixing Yang; Sidong Liu; Maurice Pagnucco; Antonio Di Ieva; Shlomo Berkovsky; Yang Song 001 (MLMI@MICCAI, 2022)

Weak label based Bayesian U-Net for optic disc segmentation in fundus images. - Hao Xiong 001; Sidong Liu; Roneel V. Sharan; Enrico W. Coiera; Shlomo Berkovsky (Artif. Intell. Medicine, 2022)

Semi-supervised breast histopathological image classification with self-training based on non-linear distance metric. - Kun Liu 020; Zhuolin Liu; Sidong Liu (IET Image Process., 2022)

Spherical coordinates transformation pre-processing in Deep Convolution Neural Networks for brain tumor segmentation in MRI. - Carlo Russo; Sidong Liu; Antonio Di Ieva (Medical Biol. Eng. Comput., 2022)

Colour adaptive generative networks for stain normalisation of histopathology images. - Cong Cong; Sidong Liu; Antonio Di Ieva; Maurice Pagnucco; Shlomo Berkovsky; Yang Song 001 (Medical Image Anal., 2022)

Medical Image Classification Based on Semi-Supervised Generative Adversarial Network and Pseudo-Labelling. - Kun Liu 020; Xiaolin Ning; Sidong Liu (Sensors, 2022)

SoftMatch: Comparing Scanpaths Using Combinatorial Spatio-Temporal Sequences with Fractal Curves. - Robert Ahadizad Newport; Carlo Russo; Sidong Liu; Abdulla Al Suman; Antonio Di Ieva (Sensors, 2022)

Domain-Specific Pre-training Improves Confidence in Whole Slide Image Classification. - Soham Rohit Chitnis; Sidong Liu; Tirtharaj Dash; Tanmay Tulsidas Verlekar; Antonio Di Ieva; Shlomo Berkovsky; Lovekesh Vig; Ashwin Srinivasan 001 (EMBC, 2023)

A Deep Learning Framework for Skull Stripping in Brain MRI. - Mehnaz Tabassum; Abdulla Al Suman; Carlo Russo; Antonio Di Ieva; Sidong Liu (EMBC, 2023)

Trainable Prototype Enhanced Multiple Instance Learning for Whole Slide Image Classification. - Litao Yang; Deval Mehta; Sidong Liu; Dwarikanath Mahapatra; Antonio Di Ieva; Zongyuan Ge (MIDL, 2023)

Domain-Specific Pretraining Improves Confidence in Whole Slide Image Classification. - Soham Rohit Chitnis; Sidong Liu; Tirtharaj Dash; Tanmay Tulsidas Verlekar; Antonio Di Ieva; Shlomo Berkovsky; Lovekesh Vig; Ashwin Srinivasan 001 (CoRR, 2023)

TPMIL: Trainable Prototype Enhanced Multiple Instance Learning for Whole Slide Image Classification. - Litao Yang; Deval Mehta; Sidong Liu; Dwarikanath Mahapatra; Antonio Di Ieva; Zongyuan Ge (CoRR, 2023)

Towards Machine Learning-based Quantitative Hyperspectral Image Guidance for Brain Tumor Resection. - David G. Black; Declan Byrne; Anna Walke; Sidong Liu; Antonio Di Ieva; Sadahiro Kaneko; Walter Stummer; Septimiu E. Salcudean; Eric Suero Molina (CoRR, 2023)

Decoupled Optimisation for Long-Tailed Visual Recognition. - Cong Cong; Shiyu Xuan; Sidong Liu; Shiliang Zhang; Maurice Pagnucco; Yang Song 001 (AAAI, 2024)

AI in Neuro-Oncology: Predicting EGFR Amplification in Glioblastoma from Whole Slide Images Using Weakly Supervised Deep Learning. - Homay Danaei Mehr; Imran Noorani; Priyanka Rana; Antonio Di Ieva; Sidong Liu (AIME (2), 2024)

Cross-Modality Synthesis of T1c MRI from Non-contrast Images Using GANs: Implications for Brain Tumor Research. - Mehnaz Tabassum; Priyanka Rana; Eric Suero Molina; Antonio Di Ieva; Sidong Liu (AIME (2), 2024)

Meta-Transfer Learning for Few-Shot Meningioma Segmentation. - Shenghui Yan; Sidong Liu; Antonio Di Ieva; Maurice Pagnucco; Yang Song 001 (ISBI, 2024)

When Eye-Tracking Meets Machine Learning: A Systematic Review on Applications in Medical Image Analysis. - Sahar Moradizeyveh; Mehnaz Tabassum; Sidong Liu; Robert Ahadizad Newport; Amin Beheshti; Antonio Di Ieva (CoRR, 2024)

Dataset Distillation for Histopathology Image Classification. - Cong Cong; Shiyu Xuan; Sidong Liu; Maurice Pagnucco; Shiliang Zhang; Yang Song 001 (CoRR, 2024)

Implementation and Application of an Intelligibility Protocol for Interaction with an LLM. - Ashwin Srinivasan; Karan Bania; Shreyas V; Harshvardhan Mestha; Sidong Liu (CoRR, 2024)

Diagnostic Performance of Deep Learning for Predicting Gliomas' IDH and 1p/19q Status in MRI: A Systematic Review and Meta-Analysis. - Somayeh Farahani; Marjaneh Hejazi; Mehnaz Tabassum; Antonio Di Ieva; Neda Mahdavifar; Sidong Liu (CoRR, 2024)

Adaptive unified contrastive learning with graph-based feature aggregator for imbalanced medical image classification. - Cong Cong; Sidong Liu; Priyanka Rana; Maurice Pagnucco; Antonio Di Ieva; Shlomo Berkovsky; Yang Song 001 (Expert Syst. Appl., 2024)

Emerging Applications and Translational Challenges for AI in Healthcare. - Sidong Liu; Cristian Castillo-Olea; Shlomo Berkovsky (Inf., 2024)

Adaptive Clustering for EGFR Amplification Prediction in Glioblastoma: A Variational Autoencoder-Dirichlet Bayesian Gaussian Approach. - Homay Danaei Mehr; Cong Cong; Imran Noorani; Antonio Di Ieva; Sidong Liu (AIME (1), 2025)

Stain Imputation in Multiplex Immunofluorescence Imaging (SIMIF) Based on Random Channel-Wise Masking. - Xingnan Li; Priyanka Rana; Tuba N. Gide; Nurudeen A Adegoke; Yizhe Mao; Georgina V. Long; Richard A. Scolyer; Shlomo Berkovsky; Enrico W. Coiera; James S. Wilmott; Sidong Liu (ISBI, 2025)

Multi-Sequence MRI to Multi-Tracer Pet Generation via Diffusion Model. - Wenjin Zhong; Cong Cong; Ghasem Azemi; Mehnaz Tabassum; Antonio Di Ieva; Sidong Liu (ISBI, 2025)

Towards a Multimodal MRI-Based Foundation Model for Multi-Level Feature Exploration in Segmentation, Molecular Subtyping, and Grading of Glioma. - Somayeh Farahani; Marjaneh Hejazi; Antonio Di Ieva; Emad Fatemizadeh; Sidong Liu (CoRR, 2025)

VaxGuard: A Multi-Generator, Multi-Type, and Multi-Role Dataset for Detecting LLM-Generated Vaccine Misinformation. - Syed Talal Ahmad; Haohui Lu; Sidong Liu; Annie Lau; Amin Beheshti; Mark Dras; Usman Naseem (CoRR, 2025)

Hypergraph Tversky-Aware Domain Incremental Learning for Brain Tumor Segmentation with Missing Modalities. - Junze Wang; Lei Fan 007; Weipeng Jing 001; Donglin Di; Yang Song 001; Sidong Liu; Cong Cong (CoRR, 2025)

FoundBioNet: A Foundation-Based Model for IDH Genotyping of Glioma from Multi-Parametric MRI. - Somayeh Farahani; Marjaneh Hejazi; Antonio Di Ieva; Sidong Liu (CoRR, 2025)