Published, accepted or in revision
2024
4. Yuan K, Wang L, Wei Q*, Cheng X*, Zhao C, Tang S, Deng HW, Zhou W. A deep learning approach based on two-channel 3DCNN networks to automatically predict the risk of femoral fracture using CT images. Journal of Imaging Science and Technology. 2024.
3. Zhu F, Tian Y, Han C, Li Y, Nan J, Yao N*, Zhou W*. Model-level Attention and Batch-instance Style Normalization for Federated Learning on Medical Image Segmentation. Information Fusion. 2024.
2. Zhao C, Liu A, Zhang X, Cao X, Ding Z, Sha Q, Shen H, Deng HW*, Zhou W*. CLCLSA: Cross-omics linked embedding with contrastive learning and self attention for integration with incomplete multi-omics data. Computers in Biology and Medicine. 2024.
1. Cao X, Keyak JH, Sigurdsson S, Zhao C, Zhou W, Liu A, Lang TF, Deng HW, Gudnason V*, Sha Q*. A new hip fracture risk index derived from FEA-computed proximal femur fracture loads and energies-to-failure. Osteoporosis International. 2024.
2023
13. Zhao C, Keyak JH, Cao X, Sha Q, Tian Q, Qiu C, Su R, Wu L, Luo Z, Zhao L, Shen H, Deng HW*, Zhou W*. Multi-view information fusion using multi-view variational autoencoders to predict proximal femoral strength. Frontiers in Endocrinology Sec. Bone Research. 2023.
12. Zhao C, Shi S, He Z, Malhotra S, Wang C, Zhao Z, Li X, Wen H, Tang S, Zhou Y*, Zhou W*. Spatial-temporal V-Net for automatic segmentation and quantification of right ventricle on gated myocardial perfusion SPECT images. Medical Physics. 2023.
11. He Z, Si H, Zhang X, Chen QH, Zou J*, Zhou W*. A new method using deep transfer learning on ECG to predict the response to cardiac resynchronization therapy. Medical Imaging Process & Technology. 2023.
10. Zhao C, Xu Z, Hung GU, Zhou W*. EAGMN: Coronary Artery Semantic Labeling using Edge Attention Graph Matching Network. Computers in Biology and Medicine. 2023.
9. Zhao Z, Wang C, Peng Z, Bu J, Li C, Li D, Zhou W, Lu R*, Tang L*, Li Y*. Deep-learning-based Image Segmentation for Image-based Computational Hemodynamic Analysis of Abdominal Aortic Aneurysms: A Comparison Study. The influence of arm positions on mechanical dyssynchrony measured by gated myocardial perfusion imaging. Quantitative Imaging in Medicine and Surgery. 2023.
8. Lyu Z, King K, Rezaeitaleshmahalleh M, Pienta D, Mu N, Zhao C, Zhou W, Jiang J*. Deep-learning-based Image Segmentation for Image-based Computational Hemodynamic Analysis of Abdominal Aortic Aneurysms: A Comparison Study. Biomedical Physics & Engineering Express. 2023.
7. Rezaeitaleshmahalleh M, Mu N, Lyu Z, Zhou W, Zhang X, Rasmussen TE, McBane II RD, Jiang J*. Radiomic-based Textural Analysis of Intraluminal Thrombus in Aortic Abdominal Aneurysms: A Demonstration of Automated Workflow. Journal of Cardiovascular Translational Research. 2023.
6. Zhao C, Xu Z, Jiang J, Esposito M, Pienta D, Hung GU, Zhou W*. AGMN: Association Graph-based Graph Matching Network for Coronary Artery Semantic Labeling on Invasive Coronary Angiograms. Pattern Recognition. 2023.
5. Yao N, Li L, Gao Z, Zhao C, Li Y, Han C, Nan J, Zhu Z, Xiao Y, Zhu F, Zhao M*, Zhou W. Deep Learning-Based Diagnosis of Disease Activity in Patients with Graves’ Orbitopathy Using Orbital SPECT/CT. European Journal of Nuclear Medicine and Molecular Imaging. 2023.
4. Meng Y, Du Z, Zhao C, Dong M, Pieta D, Tang J*, Zhou W*. Automated extraction of coronary arteries in invasive coronary angiograms. Technology and Health Care. 2023.
3. Fernandes F, Larsen K, He Z, Nascimento E, Peix A, Sha Q, Paez D, Garcia EV, Zhou W*, Mesquita CT*. A new method using machine learning to integrate ECG and gated SPECT MPI for Cardiac Resynchronization Therapy Decision Support. European Journal of Nuclear Medicine and Molecular Imaging. 2023. [PMID: 37195444]
2. Zhu F, Li L, Zhao J, Zhao C, Tang S, Nan J, Li Y, Zhao Z, Shi J, Chen Z, Han C, Jiang Z*, Zhou W*. A new method incorporating deep learning with shape priors for left ventricular segmentation in myocardial perfusion SPECT images. Computers in Biology and Medicine. 2023. [PMID: 37130501]
1. Zhu F, Wang G, Zhao C, Malhotra S, Zhao M, He Z, Shi J, Jiang Z*, Zhou W*. Automatic reorientation by deep learning to generate short-axis SPECT myocardial perfusion images. Journal of Nuclear Cardiology. 2023.
2022
14. Song M, Greenbaum J, Joseph Luttrell J IV, Zhou W*, Wu C, Luo Z, Qiu C, Zhao LJ, Su KJ, Tian Q, Shen H, Hong X, Gong P, Shi X, Deng HW, Zhang C. An Autoencoder-Based Deep Learning Method for Genotype Imputation. Frontiers in Artificial Intelligence, section Medicine and Public Health.2022.
13. Zhao C, Tang H, McGonigle D, He Z, Zhang C, Wang YP, Deng HW, Bober R*, Zhou W*. Development of an approach to extracting coronary arteries and detecting stenosis in invasive coronary angiograms. Journal of Medical Imaging. 2022.
12. Zhu F, Gao Z, Zhao C, Zhu H, Tian Y, Dong Y, Jiang J, Dai N*, Zhou W. A Deep Learning-based Method to Extract Lumen and Media-Adventitia in Intravascular Ultrasound Images. Ultrasonic Imaging. 2022.
11. He Z, Zhang X, Zhao C, Ling X, Malhotra S, Qian Z, Wang Y, Hou X, Zou J*, Zhou W*. A method using deep learning to discover new predictors of CRT response from mechanical dyssynchrony on gated SPECT MPI. Journal of Nuclear Cardiology. 2022.
10. Wang G, Zhu F, Zhao C, Malhotra S, Jiang Z, Zhou W. Automatic reorientation by deep learning to generate short-axis SPECT myocardial perfusion images. ASNC 2022.(Conference abstract)
9. Zou F, Qian Z, Qin C, Xue S, Zhang X, Qiu Y, Hou X, Zhou W, Zou J. Complete electrical reverse remodeling of native conduction after resynchronization therapies. HRS 2022.(Conference abstract)
8. Cao X, Keyak JH, Sigurdsson S, Zhao C, Zhou W,Lang T, Deng HW, Gudnason V, Sha Q. Hip Fracture Prediction using the First Principal Component Derived from FEA-Computed Fracture Loads. ASBMR 2022.(Conference abstract)
7. Zhao C, Bober R, Tang H, Tang J, Dong M, Zhang C, He Z, Esposito ML, Xu Z*, Zhou W*. Semantic segmentation to extract coronary arteries in fluoroscopy angiograms. Journal of Advances in Applied & Computational Mathematics. 2022.
6. Wang C, Ma Y, Liu Y, Cui C, Qin H, Zhao Z, Li C, Ju W, Chen M, Li D*, Zhou W*. Texture Analysis of SPECT Myocardial Perfusion Provides Prognostic Value for Dilated Cardiomyopathy. Journal of Nuclear Cardiology. 2022.
5. Hu X, Qian Z, Zou F, Xue S, Zhang X, Wang Y, Hou X, Zhou W, Zou J*. A mild dyssynchronous contraction pattern detected by SPECT myocardial perfusion imaging predicts super-response to cardiac resynchronization therapy. Frontiers in Cardiovascular Medicine. 2022.
4. Qian Z, Qin C, Zou F, Xue S, Wang Y, Zhang X, Qiu Y, Wu H, Hou X, Zhou W, Zou J*. Complete electrical reverse remodeling of native conduction after resynchronization therapies. International Journal of Cardiology. 2022.
3. Deng Y, Wang L, Zhao C, Tang S*, Cheng X, Deng HW, Zhou W. A Deep Learning-Based Approach to Automatic Proximal Femur Segmentation in Quantitative CT Images. Medical and Biological Engineering and Computing. 2022.
2. Meng Y, Dong M, Dai X, Tang H, Zhao C, Jiang J, Xu S, Zhou Y, Zhu F, Xu Z*, Zhou W*. Automatic Identification of End-Diastolic and End-Systolic Cardiac Frames from Invasive Coronary Angiography Videos. Technology and Health Care. 2022.
1. Xu Z, Tang H, Malhotra S, Dong M, Zhao C, Ye Z, Zhou Y, Xu S, Li D, Wang C*, Zhou W*. Three-dimensional Fusion of Myocardial Perfusion SPECT and Invasive Coronary Angiography Guides Coronary Revascularization. Journal of Nuclear Cardiology. 2022. [PMID: 35194752]
2021
13. Lindquist EM, Gosnell JM, Khan SK, Byl JL, Zhou W, Jiang J, Vettukattil JJ*. 3D Printing in Cardiology: A Review of applications and roles for advanced cardiac imaging. Annals of 3D Printed Medicine. 2021.
12. Zheng D, Liu Y, Zhang L, Hu F, Tan X, Jiang D, Zhou W, Lan X, Qin C*. Incremental Value of Left Ventricular Mechanical Dyssynchrony Assessment by Nitrogen-13 ammonia ECG-Gated PET in Patients with Coronary Artery Disease. Frontiers in Cardiovascular Medicine, section Cardiac Rhythmology. 2021.
11. He Z, Li D, Cui C, Qin HY, Zhao Z, Hou X, Zou J, Chen ML, Wang C*, Zhou W*. Predictive values of left ventricular mechanical dyssynchrony for CRT response in heart failure patients with different pathophysiology. Journal of Nuclear Cardiology. 2021.
10. Zhao C, Vij A, Malhotra S, Tang J, Tang H, Pienta D, Xu Z*, Zhou W*. Automatic extraction and stenosis evaluation of coronary arteries in invasive coronary angiograms. Computers in Biology and Medicine. 2021.
9. Zhu F*, Gao Z, Zhao C, Zhu Z, Liu Y, Tang S, Jiang C, Li X, Zhao M*, Zhou W. Semantic Segmentation Using Deep Learning to Extract Total Extraocular Muscles for Orbital Computed Tomography Images. Optik. 2021: 244; 167551.
8. Wang CY, Hung GW, Lo HC, Tsai SC, He Z, Zhang X, Chiang KF, Zou J*, Zhou W*, Huang JL*, Chen SA. Clinical Impacts of Scar Reduction on Gated Myocardial Perfusion SPECT after Cardiac Resynchronization Therapy. Journal of Nuclear Cardiology. 2021.
7. Hung GU, Zou J, He Z, Zhang X, Tsai SC, Wang CY, Chiang KF, Tang H, Garcia EV, Zhou W*,Huang JL*. Left-ventricular dyssynchrony in viable myocardium by myocardial perfusion SPECT is predictive of mechanical response to CRT. Annals of Nuclear Medicine. 2021.
6. Zhao C, Keyak JH, Tang J, Kaneko TS, Khosla S, Amin S, Atkinson EJ, Zhao LJ, Serou MJ, Zhang C, Shen H, Deng HW*, Zhou W*. SP-V-Net: Incorporating shape priors into convolutional neural networks for automatic segmentation of proximal femur from quantitative CT images. Complex & Intelligent Systems. 2021.
5. Zhao C, Xu Y, He Z, Tang J*, Zhang Y, Han J, Shi Y*, Zhou W*. A New Approach for Lung Segmentation and Automatic Detection of COVID-19 Using Radiomic Features from Chest CT Images. Pattern Recognition. 2021.
GitHub (open-sourced): https://github.com/MIILab-MTU/KD4COVID19
4. Wen H, Wei Q, Huang JL, Tsai SC, Wang Cy, Chiang KF, Deng Y, Cui X, Gao R, Zhou W, Huang GU*, Tang S*. Analysis on SPECT Myocardial Perfusion Imaging with A Tool Derived from Dynamic Programming to Deep Learning. Optik. 2021.
3. Wang KS, Yu G, Xu C, Meng XH, Zhou J, Zheng C, Deng Z, Shang L, Liu R, Su S, Zhou X, Li Q, Li J, Wang J, Ma K, Qi J, Hu Z, Tang P, Qiu X, Li BY, Shen WD, Quan RP, Yang JT, Huang LY, Xiao Y, Yang ZC, Li Z, Wang SC, Ren H, Liang C, Guo W, Li Y, Xiao H, Gu Y, Huang ZC, Huang J, Zhang C, Zhou W,Zhang K, Yi C, Shen H, Wang YP, Xiao HM*, Deng HW*. Accurate Diagnosis of Colorectal Cancer Based on Histopathology Images Using Deep Learning Artificial Intelligence. BMC Medicine. 2021.
2. Shi J, Zhou Y, Kata P, Seeburun S, Wang C, Li D, Jiang Z*, Zhou W. Comparison of left ventricular dyssynchrony parameters between exercise and adenosine triphosphate stress test using gated SPECT myocardial perfusion imaging. Kardiologia. 2021.
1. Tang H, Bober R, Zhao C, Zhu H, Zhang C, Zhu H, He Z, Xu Z*, Zhou W*. 3D Fusion between Fluoroscopy Angiograms and SPECT Myocardial Perfusion Images to Guide Percutaneous Coronary Intervention. Journal of Nuclear Cardiology. 2021.
2020
11. He Z, Fernandes FA, Nascimenta EA, Garcia EV, Mesquita CT*,Zhou W*. Incremental value of left ventricular shape parameters measured by gated SPECT MPI in predicting CRT super-responders. Journal of Nuclear Cardiology. 2020.
10. Jiang W, Liu Y, He Z, Zhou Y, Wang C, Jiang Z*, Zhou W. Prognostic value of left ventricular mechanical dyssynchrony in hypertrophic cardiomyopathy patients with low to moderate risk of sudden cardiac death. Nucearl Medicine Communications. 2020.
9. Zhou Y, He Z, Liao S, Liu Y, He Z, Zhang L, Zhu X, Cheang I, Zhang H, Yao W, Li X*, Zhou W. Prognostic value of integrated analysis of electrical and mechanical dyssynchrony in patients with acute heart failure. Journal of Nuclear Cardiology. 2020.
8. Hua X, Han J*, Zhao C, Tang H, He Z, Tang J, Chen QH, Tang S, Zhou W*, Tang J*. A Novel Method for ECG Signal Classification via an Enhanced One-Dimensional Convolutional Neural Network. Multimedia Systems. 2020.
Preprint: https://arxiv.org/abs/2006.11655
Download open-source codes: https://github.com/MIILab-MTU/ECGTools
7. Song M, Greenbaum, Luttrell J, Gong P, Zhou W, Shen H, Zhang C*, Deng H*. A Review of Integrative Imputation for Multi-Omics Datasets. Frontiers in Genetics. 2020.
6. Zhu F, Xu D, Liu Y, Lou K, He Z, Zhang H, Sheng Y, Yang R, Li X, Kong X, Zhang H*, Zhou W. Machine learning for the diagnosis of pulmonary hypertension. Journal Kardiologia. 2020.
5. Wang C, Shi J, Tang H, He Z, Liu Y, Zhao Z, Li C, Gu K, Hou X, Chen M, Zou J, Zhou L*, Garcia EV, Li D*, Zhou W*. Left Ventricular Systolic and Diastolic Dyssynchrony to Improve Cardiac Resynchronization Therapy Response in Heart Failure Patients with Dilated Cardiomyopathy. Journal of Nuclear Cardiology. 2020.
4. Qian Z, Wang Y, Hou X, Qiu Y, Jiang Z, Wu H, Zhao Z, Zhou W, Zou J*. A pilot study to determine if left ventricular activation time is a useful parameter for left bundle branch capture: validated by ventricular mechanical dyssynchrony with SPECT imaging. Journal of Nuclear Cardiology. 2020.
3. Zhu F, Li X, Tang H, He Z, Zhang C, Hung GW, Chiu PY*, Zhou W*. Machine learning for the preliminary diagnosis of senile dementia. Scientific Programming. 2020.
2. Zhang F, Wang J, Shao X, Yang M, Qian Y, Yang X, Wu Z, Li S, Xin W, Shi Y, Liu B, Yu W, He Z, Zhou W*, Wang Y*. Incremental value of myocardial wall motion and thickening to perfusion alone by gated SPECT myocardial perfusion imaging for viability assessment in patients with ischemic heart failure. Journal of Nuclear Cardiology. 2020.
1. Zhu F, Li X, McGonigle D, Tang H, He Z, Zhang C, Hung GW, Qiu PY*, Zhou W*. Analyze Informant-based Questionnaire for The Early Diagnosis of Senile Dementia Using Deep Learning. IEEE Journal of Translational Engineering in Health and Medicine. 2020.
2019
13. Hou X, Qian Z, Wan Y, Qiu Y, Chen X, Jiang H, Jiang Z, Wu H, Zhao Z, Zhou W, Zou J*. Feasibility and cardiac synchrony of permanent left bundle branch pacing through the interventricular septum. EP Europace. euz188. 2019.
12. He Z, Garcia EV, Zhou W*. Chapter 24. Nuclear imaging guiding cardiac resynchronization therapy in Nuclear Cardiology: Basic and Advanced Concepts in Clinical Practice. Springer-Nature. Book chapter. 2019. (book chapter)
11. Song M, Greenbaum J, Luttrell J, Zhou W, Deng HW, Zhang C. Imputation of Genome-Wide Association Study Data Using Autoencoders. MS IDeA conference. 2019. (conference abstract)
10. Wang C, Shi J, Zhao Z, Li C, Li D,Zhou W. Left ventricular systolic and diastolic dyssynchrony to predict cardiac resynchronization therapy response in heart failure patients with dilated cardiomyopathy. ASNC 2019. (conference abstract)
9. Deng Z, Zhao M, Liu Y, Zhu F, Zhou W, Li X. Texture analysis on myocardial perfusion SPECT to diagnose myocarditis. Society of Nuclear Medicine and Molecular Imaging. 2019. (conference abstract)
8. Zhang X, Qian Z, Tang H, Hua W, Su Y, Xu G, Liu X, Xue X, Fan J, Cai L, Zhu L, Wang Y, Hou X, Garcia EV, Zhou W*, Zou J*. A new method to recommend left-ventricular lead positions for improved CRT volumetric response and long-term prognosis. Journal of Nuclear Cardiology. 2019.
7. Wang J, Wang Y*, Yang M, Shao S, Tian Y, Shao X, Fan S, Zhang F, Yang W, Xin W, Tang H, Xu M, Yang L, Wang X, Zhou W. Mechanical contraction to guide CRT left-ventricular lead placement instead of electrical activation in myocardial infarction with left ventricular dysfunction: an experimental study based on non-invasive gated myocardial perfusion imaging and invasive electroanatomic mapping. Journal of Nuclear Cardiology. 2019.
6. Meng F, Zhang Z, Hou X, Qian Z, Wang Y, Chen Y, Wang Y, Zhou Y, Chen Z, Zhang X, Yang J, Zhang J, Guo, J, Li K, Xu G, Zhuang R, Jiang H, Zhou W, Tang S, Wei Y, Zou J*.Machine learning for prediction of sudden cardiac death in heart failure patients with low left ventricular ejection fraction: study protocol for a retro-prospective multicenter registry in China. BMJ Open. 2019.
5. Xin W, Yang X, Wang J, Shao X, Zhang F, Tang H, Wang Y*, Zhou W.Gated SPECT myocardial perfusion imaging is superior to CT attenuation-correction in discriminating myocardial infarct from attenuation artifacts in men and right CAD. Nuclear Medicine Communications. 2019.
4. Chiu PY, Tang H, Zhang C, Hung GW*, Zhou W*. The NMD-12Q: a machine learning derived brief screening instrument to detect mild cognitive impairment and dementia. PLOS One. 2019. ( download data)
3. Wang T, Yang L, Tang H, He Z, Castillo R, Wang C, Li D, Higgins K, Liu T, Curran WJ, Zhou W*, Yang X*.A learning-based automatic segmentation and quantification method on left ventricle in gated myocardial perfusion SPECT imaging: a feasibility study. Journal of Nuclear Cardiology. 2019;1-12. (IF 4.0)
2. McGonigle D, Zhao D, Tang H, Zhang C, He Z, Bober R, Zhou W*. Deep Learning to Extract Coronary Arteries from Fluoroscopy Angiography. Submitted to the Conference of Midsouth Computational Biology & Bioinformatics Society (MCBIOS ’2019). 2019. (conference abstract)
1. He Z, Tang H, McGonigle D, Zhang C, Jiang Z, Zhou W*. A Deep-Learning-Based Segmentation Method for Left Ventricle on Gated SPECT Myocardial Perfusion Images. Submitted to the Conference of Midsouth Computational Biology & Bioinformatics Society (MCBIOS ’2019). 2019. (conference abstract)
2018
10. Hung GU*, Zhou W*, Chen J. A perfect tool for comprehensive evaluation of myocardial perfusion and function: stress PET imaging. Nuclear Medicine Communications. Journal of Nuclear Cardiology. 2018. (invited editorial)
9. Zhou Y, Tang H, Shi J, Li D*, Zhou W*. Development and validation of a quantification toolkit to diagnose apical hypertrophic cardiomyopathy from gated SPECT MPI. Nuclear Medicine Communications. 2018;1-6.
8. Wang C, Tang H, Zhu F, Jiang Z, Shi J, Zhou Y, Garcia EV, Li D*, Zhou W*. Prognostic value of left ventricular dyssynchrony from SPECT MPI in patients with dilated cardiomyopathy. Journal of Nuclear Cardiology. 2018; 1-10. (IF 4.0)
7. Jiang Z*, Zhou W*. Left ventricular mechanical dyssynchrony for CAD diagnosis: does it have incremental clinical values? Journal of Nuclear Cardiology. 2018. (invited editorial)
6. Zhang F, Yang W, Wang Y*, Tang H, Wang J, Shao X, Wang Z, Zhang X, Yang L, Wang X, Zhou W. Is there an association between hibernating myocardium and left ventricular mechanical dyssynchrony in patients with myocardial infarction? Hellenic Journal of Nuclear Medicine. 2018; 21(1):28-34.
5. Jiang Z, Tang H, Shi J, Wang C, Li D, Zhou W*, Shan Q*. Assessment of left ventricular dyssynchrony during myocardial stunning on gated SPECT myocardial perfusion imaging. Nuclear Medicine Communications. 2018;39(8):725–731.
4. Yang W, Zhang F, Tang H, Shao X, Wang J, Wang X, Shao X, Xin W, Yang L, Zhou W*, Wang Y*. Summed thickening score by myocardial perfusion imaging: an independent predictor of left ventricular remodeling in patients with coronary artery disease. Journal of Nuclear Cardiology. 2018;1-12. (IF 4.0, featured by a published phone interview)
3. Wang T, Yang L, Tang H, Harms J, Wang C, Liu T, Curran WJ, Zhou W, Li D*, Yang X*. A learning-based automatic segmentation and quantification method on left ventricle in gated myocardial perfusion SPECT imaging. SPIE Medical Imaging 2019. 2018.
2. Tang H, Zhou H, Zhang C, Bober R, Zou J*, Zhou W*. Scale ratio ICP for the 3D registration of coronary venous anatomy with left ventricular epicardial surface to guide CRT LV lead placement. SPIE Medical Imaging 2019. 2018.
1. Jiang Z, Zhuo H, Zhu F, Tang H, Li D, Zhang C, Zhou W. Machine learning to diagnose CAD from SPECT MPI: a preliminary study. Submitted to ASNC Scientific Session. 2018. (Conference abstract)
2017
10. Tao N, Qiu Y, Tang H, Qian Z,Wu H, Zhu R, Wang Y, Hou X, Zhou W*, Zou J*. Assessment of Left Ventricular Contraction Patterns Using Gated SPECT MPI to Improve Cardiac Resynchronization Therapy Response. Journal of Nuclear Cardiology 2017; 1-10.(IF 4.0)
9. Cheng CM, Su CS, Chou P, Liao YC, Wang CY, Zhang JR, Hsieh YC, Wu TJ, Chen YW, Weng CJ, Chang KH, Zhou W, Hung GU*, Huang JL*, Nakajima K. Prediction of Both Electrical and Mechanical Reverse Remodeling by Acute ECG Changes after Cardiac Resynchronization Therapy. Circulation Journal 2017;1-7.(IF 4.1)
8. Wang C, Tang S, Tang H, Gao R,Zhou W*. A new method to automatically identify left-ventricular contours from the gated SPECT myocardial perfusion imaging. Fully 3D 2017.
7. Tang S, Huang JL, Hung GU, Tsai SC, Wang C, Li D, Zhou W*. Dynamic programming-based automatic myocardial quantification from gated SPECT myocardial perfusion imaging. Fully 3D 2017.
6. Zhou W, Tao N, Hou X, Wang Y, Folks RD, Cooke DC, Moncayo VM, Garcia EV*, Zou J*. Development and validation of an automatic method to detect the latest contracting viable left ventricular segments to assist guide CRT therapy from gated SPECT myocardial perfusion imaging. Journal of Nuclear Cardiology 2017; 1-10.(IF 4.0)
5. Zhou W*, Hung GU*. Left-ventricular mechanical dyssynchrony in the prognosis of dilated cardiomyopathy: which parameter is more useful? Journal of Nuclear Cardiology 2017;1-4. (invited editorial)(IF 4.0)
4. Tang H, Tang S,Zhou W*. A Review of Image-Guided Approaches for Cardiac Resynchronization Therapy. Arrhythmia & Electrophysiology Review 2017;6(2):69-74.
3. Tang H, Tao N, Zhang C, Zou J, Zhou W. Identifying the predictive factors of cardiac resynchronization therapy response: a comparative study using machine learning and logistic regression analysis. AHA Scientific Session 2017. (conference abstract)
2. Li D, Wang C, Tang H, Hung GU, Zhou W. Prognostic Value of LV Diastolic Dyssynchrony from SPECT MPI in Patients with DCM. ASNC 2017. (conference abstract)
1. Tao N, Tang H, Qiu Y, Zhou W, Qian Z, Wang Y, Hou X, Zou J. Assessment of left ventricular contraction patters using gated SPECT MPI to improve cardiac resynchronization therapy response. ACC 2017. (conference abstract)
2016
5. Zhou W, Jiang Z, Chen J, Li D*, Garcia EV*. Development and validation of a phase analysis tool to measure interventricular mechanical dyssynchrony from gated SPECT MPI. Journal of Nuclear Cardiology. 2016. (IF 4.0)
4. Zhou W, Garcia EV*. Nuclear image-guided approaches for CRT. Current Cardiology Reports 2016; 18(1); 1-11. (IF 2.0)
3. Allada SK, Kalluru RR, Rishel T, Zhou W. System optimization: image reconstruction and imaging configuration optimization with a multi-beam parallel digital breast tomosynthesis system. Book chapter in Digital tomosynthesis: benefits, clinical uses and limitations, Nova Publishers. (book chapter)
2. Zhou Y, Xu Y, Wang C, Jiang Z, Tang L, Li D, Hung GU,Zhou W. Development and validation of a phase analysis tool to measure right-ventricular mechanical dyssynchrony from gated FDG PET. ASNC 2016.(Conference abstract)
1. Li D, Wang C, Danda C, Jackson A, Zhou Y, Chen J, Zhou W. Interventricular mechanical dyssynchrony as assessed by phase analysis of gated SPECT MPI in patients with Wolff-Parkinson-White syndrome. SNMMI 2016. (Conference abstract)
2015
6. Wang L1, Zhou W1,*, Liang Y, Yang Y, Garcia EV, Chen J, Fang W*. Right ventricular dyssynchrony in pulmonary hypertension: phase analysis using FDG-PET imaging. J of Nuclear Cardiology 2015;12(1):69-78. (co-first author and co-corresponding author)(IF 4.0)
5. Zhou W, Lu J, Zhou O, Chen Y. Ray-tracing-based reconstruction algorithms for digital breast tomosynthesis. J. Electron. Imaging 2015; 24(2) 23-28.
4. Zhou W, Malalla N, Zhang Z, Chen Y. Computer simulation and optimization of breast tomosynthesis parallel imaging configuration and reconstruction. Int. J. Computational Biology and Drug Design 2015.
3. Zhou W, Wang L, Liang Y, Chen J, Fang W, Garcia EV. Development and validation of a phase analysis tool to measure right-ventricular mechanical dyssynchrony from gated FDG PET. ASNC 2015.(Conference abstract)
2. Zhou W, Jiang Z, Li D, Chen J, Garcia EV. Development and validation of a phase analysis tool to measure interventricular mechanical dyssynchrony from gated SPECT MPI. ASNC 2015.(Conference abstract)
1. Zhou W, Zhou Y, Folks RD, Cooke DC, Lin X, Chen J, Garcia EV. Inter-observer reproducibility of identifying the optimal CRT left ventricular lead position from SPECT MPI. ASNC 2015.(Conference abstract)
2014
6. Zhou W, Hou X, Piccinelli M, Tang X, Tang L, Cao K, Garcia E, Zou J, Chen J. 3D fusion of LV venous anatomy on fluoroscopy venograms with epicardial surface on SPECT myocardial perfusion images for guiding CRT LV lead placement. JACC: Cardiovascular Imaging 2014; 7(12): 1239-1248 (highlighted on the front cover).(IF 10.2)
5. Zhou Y, Zhou W, Folks RD, Manatunga DN, Jacobson AF, Bax JJ, Garcia EV, Chen J. I-123 mIBG and Tc-99m myocardial SPECT imaging to predict inducibility of ventricular arrhythmia on electrophysiology testing: A retrospective analysis. J of Nuclear Cardiology 2014; 21(5):913-920. (IF 4.0)
4. Zhou W, Lu J, Zhou O, Chen Y. Evaluation of back-projection methods for breast tomosynthesis image reconstruction. Journal of Digital Imaging 2014; 28(3):338-345.
3. Chen Y, Zhou W, Dobbins JT III. Fourier-domain methods for optimization of tomosynthesis (NEQ). Book chapter, in Tomosynthesis Imaging, ed. I Reiser and S Glick, Taylor & Francis, 2014. (Book chapter)
2. Zhou W, Garcia E, Chen J, et al. 3D fusion of LV venous anatomyon fluoroscopy venograms with epicardial surfaces on SPECT myocardial perfusion images for guiding CRT LV lead placement. ACC 2014.(Conference abstract)
1. Zhou W, Fang W, He Z, Chen J. Development of a phase analysis tool to measure right-ventricular and inter-ventricular mechanical dyssynchrony from myocardial images. ASNC 2014.(Conference abstract)
2013
7. Zhou Y, Zhou W, Folks RD, Manatunga DN, Jacobson AF, Bax JJ, Garcia EV, Chen J*. I-123 mIBG and Tc-99m cardiac SPECT imaging to predict inducibility of ventricular arrhythmia on electrophysiology testing. ASNC 2013.(Conference abstract)
6. Zhou W, Chen J*. I-123 MIBG imaging for predicting ventricular arrhythmia in heart failure patients. J Biomed Res 2013; 27:6:460-466.
5. Chen J, Zhou W. 123I-MIBG SPECT. Book chapter, in SPECT Technology, Procedures and Applications, ed. H Ahmadzadehfar and E Habibi. 2013. ISBN: 978-1-62808-349-1. (Book chapter)
4. Piccinelli M, Zhou W, Chen J, Cooke DC, Oshinski J, Suever J, Quyyumi AA, Garcia EV. Automated image registration of LGE-MR imaging and Tc-99m SPECT myocardial perfusion for validation of scar quantification. ASNC 2013.(Conference abstract)
3. Chen J, Zhou W, Suever J, Oshinski J, Galt JR, Garcia EV. Development of a novel quantification tool to measure transmural scar border zone by resting Tc-99m SPECT myocardial perfusion imaging. SNM 2013(Conference abstract)
2. Zhou W, Cong L, Fang J, Qian X, Lee YZ, Lu J, Zhou O, Chen Y*. Noise power spectrum and modulation transfer function analysis of breast tomosynthesis imaging. Proc. SPIE 8868, Medical Imaging 2013: Physics of Medical Imaging 86684N.
1. Rayford CE II, Zhou W, Chen Y*. Breast tomosynthesis imaging configuration analysis. International Journal of Computational Biology and Drug Design 2013; 6:3:255-62.
before 2013
11. Cong L, Zhou W, Chen Y*. Effects of slice thickness filter in filtered backprojection reconstruction with the parallel breast tomosynthesis imaging configuration. Proc. IEEE-International Symposium on Intelligent Biological Medicine. 2011.
10. Balla A, Zhou W, Chen Y. Impulse response characterization of breast tomosynthesis reconstruction with parallel imaging configurations. Proc. SPIE 7622, Medical Imaging 2010: Physics of Medical Imaging, 76225K.
9. Zhou W, Qian X, Lu J, Zhou O, Chen Y. Multi-beam X-ray source breast tomosynthesis reconstruction with different algorithms. Proc. SPIE 7622, Medical Imaging 2010: Physics of Medical Imaging, 76220H.
8. Chen Y*, Balla A, Rayford CE II, Zhou W, Fang J, Cong L. Digital tomosynthesis parallel imaging computational analysis with shift and add and back projection reconstruction algorithms. International Journal of Computational Biology and Drug Design 2010; 3(4): 287-296.
7. Chen Y*, Zhou W, Yang G, Qian X, Lu J, Zhou O. Breast tomosynthesis reconstruction with a multi-beam X-ray source. Proc SPIE 7258, Medical Imaging 2009: Physics of Medical Imaging, 725859. doi:10.1117/12.811659.
6. Chen Y*, Zhou W, Qian X, Lu J, Zhou O. Breast tomosynthesis reconstruction and optimization with a multi-beam x-ray source: preliminary results. Proceedings of Tomosynthesis Imaging Symposium 2009: Frontiers in Research and Clinical Applications.
5. Zhou W, Balla A, Chen Y. Tomosynthesis reconstruction using an accelerated expectation maximization algorithm with novel data structure based on sparse matrix ray-tracing method. International Journal of Functional Informatics and Personalized Medicine 2008; 1:4: 355-365.
4. Zhou W*, Huang J. A fast multi-level algorithm for drawing large undirected graphs. Proc. ICICSE 2008;110-117.
3. Zhou W*, Huang J. LGES: A large graph embedding system. Proc. WKDD 2008; 260-263.
2. Zhou W*, Huang J. A fast three-dimensional multilevel algorithm for drawing large general graphs. Proc. ICICA 2007; 856-859.
1. Zhou W*, Huang J, Duan Y. A genetic algorithm for drawing directed acyclic graphs. Journal of Information and Computational Science 2007; 4:4: 1119-1125.
Patents and Invention Disclosures
1. Zhou W, Li D. A new method to diagnose apical hypertrophic cardiomyopathy from gated single-photon emission computed tomography (SPECT). Invention disclosure. University of Southern Mississippi. 2016.
2. Zhou W, Li D. A new method to measure right-ventricular and interventricular mechanical dyssynchrony from gated single-photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI). Invention disclosure. University of Southern Mississippi. 2016.
3. Chen J, Zhou W. Integration of fluoroscopy venogram and myocardial perfusion SPECT image with left-ventricular contraction sequence and scar distribution. Invention Disclosure. Emory University. 2014.
4. Ehsan DM, Joerg S, Bharat R, Zhou W. Estimating position of an organ. US 61/891,521, international patent publication number: WO2015055485 A1. Philips.
5. Ehsan DM, Joerg S, Bharat R, Zhou W. System and method for lung motion prediction using a displacement driven finite element modeling scheme. Invention Disclosure. 2012. Philips.
6. Vignon F, Robert JL, Zhou W, Raduescu E, Gijsbers G. Multi-view real-time 3D transthoracic echocardiography for interventional guidance: device and methods. Invention Disclosure. 2011. Philips.
