AI in Imaging and Neuroscience Lab

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2024
  1. Nodule detection and generation on chest X-rays: NODE21 Challenge.
    Sogancioglu et al. IEEE TMI, 2024.
  2. AtPCa-Net: Anatomical-aware Prostate Cancer Detection Network on Multi-parametric MRI.
    H. Zheng et al. Scientific Reports, 2024.
  3. Prediction of Visual Field Progression with Baseline and Longitudinal Structural Measurements using Deep Learning.
    V. Mohammadzadeh et al. American Journal of Opthalmology, 2024.
  4. Identifying Multivariate Nonlinear Bias in Sammpris Using Graph-Based AI Analysis.
    A. Seyedzadeh et al. ISC, 2024.
  5. Mapping Accessibility Differences of Acute Stroke Centers in the United States.
    J. Dugan et al. ISC, 2024.
  6. 2023

  7. A Comparative Study of Open-Source Large Language Models, GPT-4 and Claude 2: Multiple-Choice Test Taking in Nephrology.
    S. Wu, NEJM AI 2023.
  8. Clinical characteristics and outcomes of patients with post-stroke epilepsy: protocol for an individual patient data meta-analysis from the International Post-Stroke Epilepsy Research Repository (IPSERR).
    N. Mishra, BMJ Open 2023.
  9. Prediction of Visual Field Progression with Serial Optic Disc Photographs Using Deep Learning.
    V. Mohammadzadeh et al. British Journal of Ophthalmology, 2023.
  10. Prediction of Central Visual Field Measures from Macular OCT Volume Scans with Deep Learning.
    V. Mohammadzadeh et al. TVST, 2023.
  11. 3D Reconstruction from 2D Cerebral Angiograms as a Volumetric Denoising Problem.
    S. Wu et al. ISVC, 2023.
  12. Foil-Net: Deep Learning-Based Wave Classification for Hydrofoil Surfing.
    Z. Mossing et al. ISVC, 2023.
  13. A Multimodal Approach for Predicting Glaucoma Progression with Artificial Intelligence.
    V. Mohammadzadeh et al. AAO Conference, 2023.
  14. Prediction of the Final Visual Fields from Earlier Visual Field Data with Artificial Intelligence.
    V. Mohammadzadeh et al. AAO Conference, 2023.
  15. Prediction of Glaucoma Progression from Earlier Visual Field Data with Deep Learning Survival Analysis.
    V. Mohammadzadeh et al. AAO Conference, 2023.
  16. Auxiliary-Domain Learning for a Functional Prediction of Glaucoma Progression.
    S. Wu et al. MICCAI - OMIA Workshop, 2023.
  17. A.I. in a Liberal Arts College: The Renaissance of Humanistic Education.
    F. Scalzo. ACM - XRDS, 2023.
  18. Mask R-CNN Assisted 2.5D Object Detection Pipeline of 68Ga-PSMA-11 PET/CT-positive Metastatic Pelvic Lymph Node After Radical Prostatectomy from solely CT Imaging.
    D. Xu et al. Scientific reports, 2023.
  19. 2022

  20. Determining and Validating Population Differences in Magnetic Resonance Angiography Using Sparse Representation.
    S. Mendoza et al. IEEE BIBM, 2022.
  21. CBFV Waveform Pattern Analysis in Ultrasound-based Noninvasive ICP Monitoring.
    M. Wei et al. IEEE BIBM, 2022.
  22. Predicting Hypoperfusion Lesion and Target Mismatch in Stroke from Diffusion-weighted MRI using Deep Learning.
    Y. Yu et al. Radiology, 2022.
  23. Hypoperfusion Lesion And Target Mismatch Prediction In Acute Ischemic Stroke From Baseline Mr Diffusion Imaging Using A 3d Convolutional Neural Network.
    Y. Yu et al. Stroke, 2022.
  24. Multiparametric MRI-based radiomics model to predict pelvic lymph node invasion for patients with prostate cancer.
    H. Zheng et al. European Radiology, 2022.
  25. Deep Learning-Based Classification of Plant Xylem Tissue from Light Micrographs.
    S. Wu et al. ISVC, 2022.
  26. Machine Learning Approach for Obstructive Sleep Apnea Screening using Brain Diffusion Tensor Imaging.
    R. Kumar et al. Journal of Sleep Research, 2022.
  27. Fully Automated Segmentation of Prostatic Urethra for MR-Guided Radiation Therapy (MRgRT).
    D. Xu et al. Medical Physics, 2022.
  28. Mapping Disparities in Availability of Epilepsy Care at the Postal Code Level in the United States.
    K. Jalaleddini et al. AES, 2022.
  29. Quantification of Infarct Core Signal using CT Imaging in Acute Ischemic Stroke
    U. Estrada et al. NeuroImage: Clinical, 2022.
  30. A Mobile Battery-Powered Brain Perfusion Ultrasound (BPU) Device designed for Prehospital Stroke Diagnosis
    M. Kilic et al. Neurological Research and Practice, 2022.
  31. Nonlinear Schrodinger Kernel for hardware acceleration of machine learning.
    T. Zhou et al. Journal of Lightwave Technology, 2022.
  32. Weakly-supervised Convolutional Neural Networks for Vessel Segmentation in Cerebral Angiography.
    A. Vepa et al. WACV, 2022.
  33. 2021

  34. Machine Learning in Neuroimaging.
    C. Federau et al. Frontiers in Neurology, 2021.
  35. Heterogeneity between proximal and distal aspects of occlusive thrombi on pretreatment imaging in acute ischemic stroke.
    T. Hashimoto et al. NRJ, 2021.
  36. Reduced Leukoaraiosis, Non-Cardiac Embolic Stroke Etiology, and Shorter Thrombus Length Indicate Good Leptomeningeal Collateral Flow in Embolic Large Vessel Occlusion
    T. Hashimoto et al. AJNR, 2021.
  37. CT Perfusion Imaging of the Brain with Machine Learning.
    K. Cheng et al. ISVC, 2021.
  38. BERTHop: An Effective Vision-and-Language Model for Chest X-ray Disease Diagnosis.
    M. Monajatipoor et al. ICCV - CVAMD, 2021.
  39. Digital Platform for Epilepsy Management in COVID era: Benefits in Self Management.
    M. Ranjbaran et al. ILAE, 2021.
  40. Integrative Machine Learning Prediction of Prostate Biopsy Results from Negative Multiparametric MRI.
    H. Zheng et al. JMRI, 2021.
  41. Intra-Domain Task-Adaptive Transfer Learning to Determine Acute Ischemic Stroke Onset Time.
    H. Zhang et al. Computerized Medical Imaging and Graphics, 2021.
  42. Intracranial atherosclerotic disease mechanistic subtypes drive hypoperfusion patterns.
    S. Kim et al. Journal of Neuroimaging, 2021.
  43. Chronic Cerebrovascular Damage and Acute Embolic Mechanisms Associated With Acute Leptomeningeal Collateral Flow in Embolic Large Vessel Occlusion.
    T. Hashimoto et al. ISC 2021.
  44. Automatically Predicting Modified Treatment in Cerebral Ischemia Scores From Patient Digital Subtraction Angiography Using Deep Learning.
    A. Lall et al. ISC 2021.
  45. Mechanisms of Intracranial Atherosclerotic Disease Drive Hypoperfusion Patterns.
    S. Kim et al. ISC 2021.
  46. Lambda Inference Machine: accelerating computing by nonlinear evolution of spectrally modulated data.
    T. Zhou, F. Scalzo, B. Jalali, arXiv Physics, 2021.
  47. Performance of Deep Learning and Genitourinary Radiologists in Detection of Prostate Cancer using 3 T Multi-parametric MRI.
    R. Cao. JMRI, 2021.
  48. Integrative Radiomics Models to Predict Biopsy Results for Negative Prostate MRI.
    H. Zheng, ISBI 2021.
  49. 2020

  50. Editorial: Machine Learning and Decision Support in Stroke
    D. Liebeskind and F. Scalzo. Frontiers in Neurology, 2020.
  51. Conditional GAN for Prediction of Glaucoma Progression with Macular Optical Coherence Tomography.
    O. Hassan et al. ISVC, 2020.
  52. Deep Learning for Hemorrhagic Lesion Detection and Segmentation on Brain CT Images.
    L. Li et al. IEEE Journal of Biomedical and Health Informatics (J-BHI), 2020.
  53. Perfusion Parameter Thresholds That Discriminate Ischemic Core Vary with Time from Onset in Acute Ischemic Stroke.
    T. Yoshie et al. AJNR, 2020.
  54. Using artificial intelligence for improving stroke diagnosis in emergency departments: a practical framework
    V. Abedi et al. Therapeutic Advances in Neurological Disorders, 2020.
  55. Toward Automated Classification of Pathological Transcranial Doppler Waveform Morphology via Spectral Clustering.
    S. Thorpe et al. PLOS ONE, 2020.
  56. A Comparison between Radiologists versus Deep Learning for Prostate Cancer Detection in Multi-parameter MRI.
    R. Cao et al. ISMRM, 2020. Oral Presentation.
  57. A Large-scale Perfusion Imaging Atlas Of Subacute Ischemia In MCA Atherosclerotic Stenosis.
    D. Liebeskind et al. ISC, 2020.
  58. Impaired Perfusion In Intracranial Atherosclerotic Disease Predicts Cognitive Outcomes.
    D. Liebeskind et al. ISC, 2020. Oral Presentation.
  59. Imaging Correlates Of Vascular Cognitive Impairment After Recent Ischemia In IntracranialAtherosclerosis: Evidence From SAMMPRIS.
    D. Liebeskind et al. ISC, 2020.
  60. Cerebral Blood Flow Increase After Endovascular Thrombectomy on Perfusion Weighted Image is Associated With Hemorrhagic Transformation.
    T. Yoshie et al. ISC, 2020.
  61. 2019

  62. Deep Learning Detection of Penumbral Tissue on Arterial Spin Labeling.
    K. Wang et al. Stroke, 2019.
  63. Algorithm for Reliable Detection of Pulse Onsets in Cerebral Blood Flow Velocity Signals.
    N. Canac et al. Frontiers in Neurology, 2019.
  64. Opposing CSF hydrodynamic trends found in the cerebral aqueduct and prepontine cistern following shunt treatment in patients with normal pressure hydrocephalus.
    R. Hamilton et al. Fluids Barriers CNS, 2019.
  65. Middle Cerebral Artery Plaque Hyperintensity on T2-Weighted Vessel Wall Imaging is Associated with Ischemic Stroke.
    Y. Yu et al. AJNR, 2019.
  66. Automatic Estimation of Arterial Input Function in Digital Subtraction Angiography.
    A. Liebeskind, A. Deshpande, J. Murakami, F. Scalzo. ISVC, 2019. Oral Presentation.
  67. Angio-AI: Cerebral Perfusion Angiography with Machine Learning.
    E. Feghhi, J. Tran, Y. Zhou, D. Liebeskind, F. Scalzo. ISVC, 2019. Oral Presentation.
  68. Prostate Cancer Inference via Weakly-supervised Learning using a Large Collection of Negative MRI.
    R. Cao, X. Zhong, F. Scalzo, S. Raman, K. Sung. ICCV Workshop, 2019.
  69. Prognostic value of subclinical thyroid dysfunction in ischemic stroke patients treated with intravenous thrombolysis.
    D. Liu et al. Aging-US, 2019.
  70. Hemodynamics and Stroke Risk in Intracranial Atherosclerotic Disease.
    X. Leng et al. Annals of Neurology, 2019.
  71. Objective Assessment of Beat Quality in Transcranial Doppler Measurement of Blood Flow Velocity in Cerebral Arteries.
    K. Jalaleddini et. IEEE TBME, 2019.
  72. LSTM Network for Prediction of Hemorrhagic Transformation in Acute Stroke.
    Y. Yu et al. MICCAI, 2019. Early accept - Oral Presentation (Top 3%).
  73. Predicting Ischemic Stroke Tissue Fate Using a Deep Convolutional Neural Network on Source MR Perfusion Imaging.
    K. Ho, F. Scalzo, K. Sarma, W. Speier, S. El-Saden, C. Arnold. Journal of Medical Imaging, 2019.
  74. A Machine Learning Approach for Classifying Ischemic Stroke Onset Time from Imaging.
    K. Ho, W. Speier, H. Zhang, F. Scalzo, S. El-Saden, C. Arnold. IEEE TMI, 2019.
  75. Predictive Analytics and Machine Learning in Stroke and Neuroendovascular Medicine.
    H. Saber. G. Rajah, F. Scalzo, D. Liebeskind. Neurological Research, 2019.
  76. The Utility of Google TensorFlow Inception in Classifying Clear Cell Renal Cell Carcinoma and Oncocytoma on Multiphasic CT.
    H. Coy, K. Hsieh, W. Wu, M. Nagarajan, J. Young, M. Douek, M. Brown, F. Scalzo, S. Raman. Abnominal Radiology, 2019.
  77. Pattern Recognition in Medical Decision Support. S. Asgari. Biomed Res Int, 2019.
  78. Online Learning with Spectral Regression.
    I. Ravkic, Y. Sun, F. Scalzo. Open Source Programming for Data Science and Machine Learning, 2019.
  79. Automatic Detection of Middle Cerebral Artery Plaque on T2-weighted Vessel Wall Imaging.
    Y. Yu et al. ISC, 2019.
  80. CFD Using SAMMPRIS CT Angiography Quantifies Pro-Atherogenic Shear Stress Linked with Post-Stenotic Flow Vortices.
    D. Liebeskind et al. ISC, 2019.
  81. 2018

  82. A Machine Learning Approach to Perfusion Imaging with Dynamic Susceptibility Contrast MR.
    R. Mckinley, F. Hung, R. Wiest, D. Liebeskind, F. Scalzo. Frontiers in Neurology, 2018.
  83. Performance Comparison of Knowledge-Based Dose Prediction Techniques Based on Limited Patient Data.
    A. Landers et al. Technol Cancer Res Treat, 2018.
  84. MiR-27a-3p protects against blood-brain barrier disruption and brain injury after intracerebral hemorrhage by targeting endothelial aquaporin-11.
    T. Xi et al. Journal of Biological Chemistry, 2018.
  85. Deep Transfer Learning Based Prostate Cancer Classification using 3 Tesla Multi-parametric MRI.
    X. Zhong et al. Abdominal Radiology, 2018.
  86. Skull Stripping using Confidence Segmentation Convolution Neural Network.
    K. Chen, J. Shen, F. Scalzo. ISVC, 2018.
  87. Automatic Registration of Serial Cerebral Angiography: A Comparative Review.
    A. Tang, Z. Zhang, F. Scalzo. ISVC, 2018.
  88. Association of anemia and hemoglobin decrease during acute stroke treatment with infarct growth and clinical outcome.
    S. Jung et al. Plos One, 2018.
  89. Validation of Collateral Scoring on Flat-Detector Multiphase CT Angiography in Patients with Acute Ischemic Stroke.
    I. Maier et al. Plos One, 2018.
  90. Intracranial Hypertension Detection using Machine Learning Classification of Non-invasive TCD Waveforms.
    F. Scalzo, R. Mercer, S. Wilk, R. Hamilton. Military Health System Research Symposium, 2018.
  91. Synthetic Perfusion Maps: Imaging Perfusion Deficits in DSC-MRI with Deep Learning.
    A. Hess, R. Meier, J. Kaesmacher, S. Jung, F. Scalzo, D. Liebeskind, R. Wiest, R. McKinley. MICCAI SWITCH, 2018.
  92. Elastic net ensemble classifier for event-related potential based automatic spelling.
    S. Kim, A. White, F. Scalzo, D. Collier. Biomedical Signal Processing and Control, 2018.
  93. Automatic Co-Registration of Cerebral Angiography: A Comparison of Algorithms
    A. Tang, Z. Zhang, F. Scalzo. UCLA Research Poster Day 2018. Best Poster Award.
  94. A Cross-Sectional Study on Cerebral Hemodynamics After Mild Traumatic Brain Injury in a Pediatric Population.
    C. Thibeault et al. Frontiers Neurology, 2018.
  95. Quantitative measures of EEG for prediction of outcome in cardiac arrest subjects treated with hypothermia: a literature review.
    S. Asgari, H. Moshirvazir, F. Scalzo, Ramezan-Arab N. J Clin Monit Comput, 2018.
  96. Nonsphericity Index and Size Ratio Identify Morphologic Differences between Growing and Stable Aneurysms in a Longitudinal Study of 93 Cases.
    Chien et al. et al. AJNR, 2018.
  97. Utility of Google TensorFlow Inceptionď Machine Learning to Discriminate Clear Cell Renal Cell Carcinoma from Oncocytoma on Multiphasic CT.
    Coy H, Wu W, Hsieh K, Nagarajan M, Douek M, Scalzo F, Raman SS. SAR, 2018.
  98. Diagnostic Utility of Machine Learning to Differentiate Clear Cell RCC from Oncocytoma on Routine Four-phase Multidector CT Images.
    Coy H, Nadkarni R, Nagarajan M, Douek M, Scalzo F, Raman SS. SAR 2018.
  99. Collaterals in Thrombectomy for MCA Occlusion: Mapping the Collaterome in the Trevo Retriever Registry.
    Liebeskind et al. ISC, 2018.
  100. The Prediction of the Hemorrhagic Transformation Locations After Reperfusion Therapy in Acute Stroke Patients: A Magnetic Resonance Perfusion Study Using Deep Learning.
    Yu et al. ISC, 2018.
  101. Bright Signals of MCA Plaque on T2 Weighted Vessel Wall Imaging are Associated With Ischemic Stroke.
    Yu et al. ISC, 2018.
  102. Reperfusion Into Severely Damaged Brain Tissue is Associated With Impending Parenchymal Hemorrhage in Acute Ischemic Stroke Patients.
    Yu et al. ISC, 2018.
  103. Currency of Collaterals: Validation and Clinical Utility of a Novel Imaging Paradigm for Triage to Endovascular Therapy.
    Liebeskind et al. ISC, 2018.
  104. Kernel Spectral Regression and Neural Networks Enable Regional Detection of Hemorrhagic Transformation on Multi-Modal MRI for Acute Ischemic Stroke.
    Ma et al. ISC, 2018.
  105. Chronic and Acute Hypertension in Ischemic Stroke Are Distinct Markers of Impaired Collateral Circulation.
    Liebeskind et al. ISC, 2018.
  106. Aspects versus Perfusion in the Trevo Retriever Registry: Defining the Core on the Largest Scale to Date.
    Liebeskind et al. ISC, 2018.
  107. 2017

  108. Prediction of Hemorrhagic Transformation Severity in Acute Stroke from Source Perfusion MRI.
    Y. Yu, D. Guo, M. Lou, D. Liebeskind, F. Scalzo. IEEE TBME, 2017.
  109. Incremental Kernel Spectral Regression with Fixed-Size Memory.
    I. Ravkic, F. Scalzo. SoCal ML Symposium, 2017.
  110. Incremental Spectral Regression with Fixed-Size Memory.
    I. Ravkic, F. Scalzo. Women in Machine Learning NIPS Workshop, 2017.
  111. Explainable Artificial Intelligence Model of Noninvasive Intracranial Pressure.
    F. Scalzo, R. Hamilton. ISS R&D, 2017.
  112. 3D Texture-based Kernel Regression for Characterization of Clear Cell Renal Cell Carcinoma vs. Oncocytoma on Four Phase MDCT.
    H Coy, R Nadkarni, F Scalzo, M Brown, S Raman. RSNA, 2017.
  113. Low-complexity Tracking of Neurological State using Manifold Learning.
    A. Rajagopal, S. Chandrasekaran, F. Scalzo. UC bioengineering symposium, 2017. Best Poster Award.
  114. ASL in ASPECTS-guided Machine Learning can Predict Clinical Outcome in Acute Ischemic Stroke Patients.
    S. Ma, S. Yu, D. Liebeskind, L. Yan, F. Scalzo, D. Wang. EMBC, 2017.
  115. Regional Detection of Hemorrhagic Transformation Using Kernel Spectral Regression and Neural Networks on Multi-modal MRI for Acute Ischemic Stroke.
    S. Ma, S. Yu, D. Liebeskind, L. Yan, D. Wang, F. Scalzo. EMBC, 2017. and USC Grodins BME Symposium, 2017. Best Poster Award.
  116. Regional Detection of Intracerebral Hemorrhage on Multi-modal MRI with Kernel Spectral Regression.
    S. Ma, S. Yu, D. Liebeskind, D. Wang, F. Scalzo. OHBM, 2017.
  117. Morphologic Changes in ICP Waveform Demonstrate Compliance Changes Irrespective of Intracranial Hypertension.
    M. Brown, W. Baker, F. Scalzo, A. Kofke. NACCSGBI, 2017.
  118. Real-Time Quantitative Changes in Cerebral Perfusion from Intra-Arterial Vasodilator Treatment in Cerebral Vasospasm.
    J. Weng, A. Tang, G. Duckwiler, D. Liebeskind, S. Sheth, F. Scalzo. ASNR, 2017.
  119. Longitudinal Recovery of Cerebrovascular Impairment Following Sports Related Concussion Utilizing TCD.
    C. Thibeault et al. AAN, 2017.
  120. ASPECTS Based Reperfusion Status on ASL is Associated with Clinical Outcome in Acute Ischemic Stroke Patients.
    S. Yu et al. JCBFM, 2017.
  121. Cerebral Blood Flow Velocity Pulse Onset Detection Using Adaptive Thresholding.
    S. Asgari, N. Arevalo, R. Hamilton, D. hanchey, F. Scalzo. IEEE BHI, 2017. (Oral presentation, top 14%)
  122. Multi-Delay ASL Can Identify Leptomeningeal Collateral Perfusion in Endovascular Therapy of Ischemic Stroke.
    X. Lou et al. Oncotarget, 2017.
  123. Real-Time Quantitative Changes in Cerebral Blood Flow From Intra-Arterial Vasodilator Treatment in Cerebral Vasospasm.
    S. Sheth, B. Quachtran, D. Liebeskind, J. Saver, G. Duckwiler, F. Scalzo, N. Gonzalez. ISC, 2017.
  124. Perfusion Angiography Improves Clinical Outcomes Prediction in Endovascular Stroke Therapy.
    S. Sheth, J. Weng, P. McElhinney, B. Quachtran, D. Liebeskind, J. Saver, G. Duckwiler, F. Scalzo. ISC, 2017.
  125. Regional Contribution of Salvaged Brain Tissue on Outcome in Endovascular Stroke Therapy
    S. Sheth, P. McElhinney, J. Weng, B. Quachtran, D. Ichwan, C. Liang, D. Liebeskind, J. Saver, G. Duckwiler, F. Scalzo. ISC, 2017.
  126. Spatio-temporal Flow Tractography (SFT) for Evaluation of Collateral Patterns in Acute Stroke.
    Y. Wang, D. Shattuck, J. Saver, D. Liebeskind, F. Scalzo. ISC, 2017.
  127. A Novel Collateral Metric of MCA Hemodynamics in SAMMPRIS.
    D. Liebeskind et al. ISC, 2017.
  128. CTA Collateral Gradient Mapping: Validation of a Novel Imaging Technique in Acute Ischemic Stroke.
    D. Liebeskind et al. ISC, 2017.
  129. Imaging Clot Porosity Prior to Endovascular Thrombectomy.
    D. Liebeskind et al. ISC, 2017.
  130. Collaterals and Reperfusion Mediate Blood Pressure Changes in Acute Ischemic Stroke.
    D. Liebeskind et al. ISC, 2017.
  131. 2016

  132. Perfusion Angiography in Acute Ischemic Stroke.
    F. Scalzo, D. Liebeskind. Comput Math Methods Med, 2016.
  133. Same Decision Probability in Neurocritical Care.
    F. Scalzo, A. Choi, A. Darwiche. Machine Learning for Healthcare, 2016.
  134. Extraction of Vascular Intensity Gradient on Computed Tomography Angiography.
    E. Agbayani, B. Jia, G. Woolf, D. Liebeskind, F. Scalzo. ISVC, 2016.
  135. Similarity Metric Learning for 2D to 3D Registration of Brain Vasculature.
    A. Tang, F. Scalzo. ISVC, 2016.
  136. Tensor Voting Extraction of Vessel Centerlines from Cerebral Angiograms.
    Y. Ding, M. Nicolescu, D. Farmer, Y. Wang, G. Bebis, F. Scalzo. ISVC, 2016.
  137. Vessel Detection on Cerebral Angiograms using Convolutional Neural Networks.
    Y. Fu, J. Fang, B. Quachtran, N. Chachkhiani, F. Scalzo. ISVC, 2016.
  138. A deep convolutional neural network for stroke MR perfusion parameter estimation.
    K. Ho, F. Scalzo, K. Sarma, S. El-Saden, A. Bui, C. Arnold. RSNA 2016.
  139. An Investigational CNN Model for the Detection of Clinically Significant Prostate Cancer using Multiparametric MRI of the Prostate.
    K. Sarma, X. Zhong, K. Ho, D. Margolis, F. Scalzo, K. Sung, N. Tan, C. Arnold. RSNA 2016.
  140. Detection of Intracranial Hypertension using Deep Learning.
    B. Quachtran, R. Hamilton, F. Scalzo. ICPR, 2016.
  141. A Temporal Deep Learning Approach for MR Perfusion Parameter Estimation in Stroke.
    K. Ho, F. Scalzo, K. Sarma, S. El-Saden, C. Arnold. ICPR, 2016. Best Student Paper Award Finalist.
  142. FLAIR Vascular Hyperintensity Topography, Novel Imaging Marker for Revascularization in MCA Occlusion.
    D. Liu, F. Scalzo, N. Rao, J. Hinman, D. Kim, L. Ali, J. Saver, W. Sun, Q. Dai, X. Liu, and D. Liebeskind. Stroke, in revision.
  143. Longitudinal Assessment of Cerebral Blood Flow Following mTBI using Transcranial Doppler.
    C. Thibeault, S. Wilk, M. O'Brien, S. Radhakrishnan, A. Sarraf, J. LeVangie, S. Thorpe, F. Scalzo, L. Petrossian, R. Hamilton. NeuroTrauma 2016.
  144. Normative Ranges of Transcranial Doppler Metrics.
    C. Thibeault, J. LaVangie, M. O'Brien, A. Sarraf, S. Wilk, F. Scalzo, R. Hamilton. ICP 2016.
  145. Noninvasive Intracranial Pressure Monitoring with Manifold-based Waveform Reconstruction.
    F. Scalzo, R. Hamilton, N. Gonzalez, P. Vespa, X. Hu. ICP 2016.
  146. Deep Learning of Intracranial Pressure Dynamics for Intracranial Hypertension Diagnosis.
    B. Quachtran, S. Wilk, C. Thibeault, S. Radhakrishnan, R. Hamilton, F. Scalzo. ISS R&D Conference 2016.
  147. Noise Reduction in Intracranial Pressure Signal using Causal Shape Manifolds.
    A. Rajagopal, R. Hamilton, F. Scalzo. Biomedical Signal Processing and Control 2016.
  148. Multimodal CT techniques for cerebrovascular and hemodynamic evaluation of ischemic stroke: occlusion, collaterals, and perfusion.
    B. Jia, F. Scalzo, E. Agbayani, G. Woolf, L. Liu, Z. Mia, D. Liebeskind. Expert Review of Neurotherapeutics. 2016.
  149. Deep Learning of MR Imaging Patterns in Prostate Cancer.
    N. Tan, N. Stier, N. Asvadi, A. Moshksar, S. Raman, F. Scalzo. ISMRM 2016.
  150. Detection of Prostate Cancer from Multi-parametric Regional MRI Features.
    N. Tan, A. Moshksar, N. Asvadi, S. Raman, F. Scalzo. ISMRM 2016.
  151. Hemodynamic Impact of Systolic Blood Pressure and Hematocrit Calculated by CFD in Patients with Intracranial Atherosclerosis.
    H. Nam, F. Scalzo, X. Leng, H. Ip, H. Lee, F. Fan, X. Chen, Y. Soo,Z. Miao, L. Liu, E. Feldmann, T. Leung, K. Wong, D. Liebeskind. Journal of Neuroimaging. 2016.
  152. Probabilistic Labeling of Cerebral Vasculature on MR Angiography.
    B. Quachtran, S. Sheth, J. Saver, D. Liebeskind, F. Scalzo. LNCS 2016.
  153. VESCA: Semi-Automated Segmentation of Cerebral Vasculature in Angiograms.
    N. Stier, C. Garduno, S. Sheth, G. Duckwiler, J. Saver, D. Liebeskind, F. Scalzo. ISC 2016.
  154. Hyperperfusion on Arterial Spin Labeling: Objective Decision Support using Pattern Recognition.
    F. Scalzo, S. Yu, S. Patel, D. Liebeskind, D. JJ Wang. ISC 2016.
  155. Predicting Acute Ischemic Stroke Tissue Fate using Deep Learning on Source Perfusion MRI.
    K. Ho, S. El-Saden, F. Scalzo, A. Bui, C. Arnold. ISC 2016.
  156. Automated Labeling of Cerebral Vasculature on MR Angiography Using Nonparametric Bayesian Inference.
    B. Quachtran, S. Sheth, J. Saver, D. Liebeskind, F. Scalzo. ISC 2016.
  157. Distal FLAIR Hyperintense vessels ASPECT pattern, not number, predicts outcome after endovascular therapy in acute M1-MCA occlusion patients.
    D. Liu, F. Scalzo; S. Starkman, N. Rao, J. Hinman, D. Kim, L. Ali, J. Saver, A. Noorian, K. Ng, C. Liang, S. Sheth, B. Yoo, X. Liu; D. Liebeskind. ISC 2016.
  158. Computational Fluid Dynamics of CT Angiography in SAMMPRIS Reveal Blood Flow and Vessel Interactions in Middle Cerebral Artery Stenoses.
    D. Liebeskind, F. Scalzo, G. Woolf, J. Zubak, G. Cotsonis, M. Lynn, H. Cloft, O. Zaidat, D. Fiorella, C. Derdeyn, M. Chimowitz, E. Feldmann. ISC 2016.
  159. FLAIR Ischemic Lesion Growth as a Biomarker of Intracranial Atherosclerosis in SAMMPRIS.
    D. Liebeskind, G. Woolf, G. Cotsonis, F. Scalzo, S. Prabhakaran, J. Romano, E. López-Cancio, M. Lynn, C. Derdeyn, D. Fiorella, T. Turan, M. Chimowitz, E. Feldmann. ISC 2016.
  160. Grade 2 or Partial Collaterals in IMS III: Half Full or Half Empty?
    D. Liebeskind, M. Hill, T. Jovin, B. Menon, R. Nogueira, O. Zaidat, F. Scalzo, A. Demchuk, J. Carrozzella, R. von Kummer, P. Khatri, M. Goyal, F. Al Ali, B. Yan, L. D Foster, S. Yeatts, Y. Palesch, J. Broderick, T. Tomsick, A. Yoo.ISC 2016.
  161. Vertebrobasilar Dolichoectasia is a Distinct Subtype of Intracranial Large Artery Disease: Computational Fluid Dynamics of Hemodynamic Abnormalities.
    D. Liebeskind, G. Woolf, J. Zubak, F. Scalzo, N. Sanossian. ISC 2016.
  162. Detection of Prostate Cancer based on Multi-parametric Regional MRI Features.
    N. Tan, A. Moshksar, S. Raman, F. Scalzo. SIIM 2016.
  163. Posterior Communicating Artery Flow Diversion in Middle Cerebral Artery Stroke: Angiographic Evidence from IMS III.
    D. Liebeskind, A. Demchuk, T. Jovin, B. Menon, R. Nogueira, O. Zaidat, F. Scalzo, M. Hill, J. Carrozzella, R. von Kummer, P. Khatri, M. Goyal, F. Al Ali, B. Yan, L. D Foster, S. Yeatts, Y. Palesch, J. Broderick, T. Tomsick, A. Yo. ISC 2016.
  164. Clot Size: Speaking the Same Language in Endovascular Stroke Therapy Across the Globe.
    D. Liebeskind, N. Sanossian, F. Scalzo, B. Xiang, R. Gupta, T. Jovin, G. Albers, H. Lutsep, W. Smith, M. Killer, J. Macho, O. Jansen, N. Wahlgren, R. Nogueira. ISC 2016.
  165. Proving CT Angiography of Collaterals Prior to Endovascular Therapy: TREVO & TREVO2.
    D. Liebeskind, N. Sanossian, F. Scalzo, B. Xiang, R. Gupta, T. Jovin, G. Albers, H. Lutsep, W. Smith, M. Killer, J. Macho, O. Jansen, N. Wahlgren, R. Nogueira. ISC 2016.

  166. 2015

  167. Deep Learning of Tissue Fate Features in Acute Ischemic Stroke.
    N. Stier, N. Vincent. D. Liebeskind, F. Scalzo. IEEE BIBM. 2015.
  168. Detection of Hyperperfusion on Arterial Spin Labeling using Deep Learning.
    N. Vincent, N. Stier, S. Yu, D. Liebeskind, D. JJ Wang, F. Scalzo. IEEE BIBM. 2015.
  169. DWI Lesion Patterns Predict Outcome in Stroke Patients with Thrombolysis.
    Liu D, Scalzo F, Starkman S, Rao N, Hinman J, Kim D, Ali L, Saver J, Noorian A, Ng K, Liang C, Sheth S, Yoo B, Liu X, Liebeskind D. Cerebrovasc Dis. 2015;40(5-6):279-85
  170. Objective Method for Mild Traumatic Brain Injury Diagnosis Based on Cerebrovascular Reactivity.
    M. O'Brien, R. Hamilton, C. Thibeault, F. Scalzo, S. Radhakrishnan, A. Green. AAN Sports Concussion Conference. 2015.
  171. Data Science of Stroke Imaging and Enlightenment of the Penumbra.
    F. Scalzo, M. Nour, D. Liebeskind. Frontiers in Neurology (Stroke), in press, 2015.

  172. Time for Collaterals? Evidence from 695 Endovascular Therapy Cases for Acute Stroke in ENDOSTROKE.
    D. Liebeskind, et al. ISC 2015.
  173. Probabilistic Atlasing of Acute Ischemic Stroke Topology.
    D. Ichwan, F. Scalzo, D. Liu, B. Bergsneider, A. Anderson, D. Liebeskind. ISC, 2015.
  174. Classification of DWI Lesion Patterns in Acute Ischemic Stroke using Shape Context.
    F. Scalzo, D. Liu, D. Liebeskind. ISC, 2015.
  175. Predicting Omni-directional Lesion growth in Acute Stroke using Multimodal Intensity Profiles.
    F. Scalzo, W. Chowdhury, D. Liebeskind. ISC, 2015.
  176. FACET: Fractal Angiography for Continuous Revascularization Evaluation during Thrombectomy.
    F. Scalzo, C. Thorenfeldt, S. Sheth, C. Liang, G. Duckwiler, D. Liebeskind. ISC, 2015.
  177. Coregistration of Serial Angiograms using Point Cloud Matching.
    F. Scalzo, N. Stier, J. Liu, W. Bi, D. Liebeskind. ISC, 2015.
  178. Cerebral Oxygen Extraction Fraction MRI to Assess Metabolic Changes in Acute Ischemic Stroke.
    L. Sharma et al. ISC, 2015.
  179. Infarction Patterns Predict Differential Response to Thrombolysis in Acute Middle Cerebral Artery Stroke Patients.
    D. Liu, F. Scalzo, M. Johnson, S. Starkman, N. Rao, J. Hinman, D. Kim, L. Ali, J. Saver, A. Noorian, K. Ng, C. Liang, S. Sheth, B. Yoo, X. Liu, D. Liebeskind. ISC, 2015.
  180. Different Strokes: Causality and Outcomes in the NINDS-tPA Trials.
    D. Liebeskind, A. Choi, N. Sanossian, S. Fang, A. Darwiche, F. Scalzo. ISC, 2015.
  181. Development of Patient Specific Computational Fluid Dynamics Model of Intracranial Arterial Stenosis.
    M. Connolly, F. Scalzo, R. Hamilton, R. Liou, X. Hu, D. Liebeskind, N. Gonzalez. ISC, 2015.
  182. Collateral Grade Drives the Importance of Time to Reperfusion in the Stentriever Era: The ENDOSTROKE Registry.
    D. Liebeskind, J. Berkefeld, K. Niederkorn, H. Deutschmann, A. Reich, M. Wiesmann, K. Gröschel, S. Boor, C. Nolte, G. Bohner, T. Neumann-Haefelin, E. Hofmann, A. Stoll, A. Bormann, F. Scalzo, C. Weimar, M. Schlamann, O. Singer. ISC, 2015.
  183. Arterial Spin Labeled MRI Quantifies Cerebral Blood Flow Changes with Blood Pressure from Acute to Subacute Stroke.
    D. Liebeskind, D. Ichwan, S. Yu, F. Scalzo, M. Johnson, J. Qiao, J. Alger, L. Ali, D. Kim, J. Hinman, N. Rao, J. Saver, B. Yoo, P. Vespa, N. Sanossian, M. Blanco, D. Wang. ISC, 2015.
  184. Detection of Early Ischemia Varies Extensively with Topography: Concurrent CT versus DWI ASPECTS.
    D. Liebeskind, S. Sheth, F. Mehrkhani, S. Kamalian, F. Scalzo, M. Johnson, M. Lev, A. Yoo. ISC, 2015.
  185. Perfusion Imaging of Intracranial Atherosclerotic Disease in SAMMPRIS.
    D. Liebeskind, C. Derdeyn, N. Sanossian, G. Cotsonis, F. Scalzo, S. Prabhakaran, J. Romano, T. Turan, M. Johnson, M. Lynn, D. Fiorella, D.Hess, M. Chimowitz, E. Feldmann. ISC, 2015.
  186. Time and Tissue: Imaging of Early Ischemia in FAST-MAG.
    D. Liebeskind, N. Sanossian, S. Starkman, P. Villablanca, A. Burgos, F. Scalzo, M. Johnson, M. Eckstein, S. Stratton, F. Pratt, R. Conwit, S. Hamilton, J. Saver. ISC, 2015.
  187. Unique ASPECTS of Conditioning? Prior TIA or Atrial Fibrillation and Early CT Findings in FAST-MAG.
    D. Liebeskind, N. Sanossian, S. Starkman, P. Villablanca, A. Burgos, F. Scalzo, M. Johnson, M. Eckstein, S. Stratton, F. Pratt, R. Conwit, S. Hamilton, J. Saver. ISC, 2015.
  188. 2B or Not to Be? Defining Successful Reperfusion In IMS III.
    D. Liebeskind, A. Yoo, T. Jovin, F. Scalzo, R. Nogueira, O. Zaidat, J. Carrozzella, R. von Kummer, A. Demchuk, L. Foster, Y. Palesch, J. Broderick, T. Tomsick. ISC, 2015.
  189. Automation and Quantification of the Angiographic Capillary Blush in Patients with Acute Ischemic Stroke undergoing Endovascular Intervention.
    J. Tarpley, F. Scalzo, J. Alger, A. Aghaebrahim, C. Liang, S. Sheth, R. Noorian, K., T. Jovin, G. Duckwiler, D. Liebeskind. ISC, 2015.
  190. Time is Brain on the Collateral Clock! Collaterals and Reperfusion Determine Tissue Injury.
    D. Liebeskind, D. Liu, N. Sanossian, S. Sheth, C. Liang, M. Johnson, L. Ali, D. Kim, J. Hinman, N. Rao, S. Starkman, R. Jahan, N. Gonzalez, S. Tateshima, G. Duckwiler, J. Saver, B. Yoo, J. Alger, F. Scalzo. ISC, 2015.
  191. Time for Collaterals? Evidence from 695 Endovascular Therapy Cases for Acute Stroke in ENDOSTROKE.
    D. Liebeskind, et al. ISC, 2015.
  192. Impact Of Systolic Blood Pressure On Cerebral Hemoynamics Measure By Computational Fluid Dynamics In Patients With Intracranial Atherosclerosis.
    H. Nam, F. Scalzo, X. Leng, M. Johnson, H. Ip, F. Fan, X, Chen, Y. Soo, Z. Miao, L. Liu, E. Feldmann, T. Leung, K. Sing Wong, D. Liebeskind. ISC, 2015.
  193. Baseline Predictors of the Malignant Collateral Profile in IMS III.
    D. Liebeskind, T. Jovin, B. Menon, R. Nogueira, O. Zaidat, F. Scalzo, M. Hill, A. Demchuk, J. Carrozzella, R. von Kummer, P. Khatri, M. Goyal, F. Al Ali, B. Yan, L. Foster, S. Yeatts, Y. Palesch, J. Broderick, T. Tomsick, A. Yoo. ISC, 2015.
  194. Ischemic Stroke in the Post-Operative Phase of 2,035 Consecutive Orthotopic Liver Transplantations.
    D. Liebeskind, C. Lening, O. Aksoy, D. Liu, J. Hinman, F. Scalzo, M. Johnson, V. Xia, R. Busuttil, V. Agopian. ISC, 2015.

  195. 2014

  196. CFD of CTA to Detect the Hemodynamic Impact of Intracranial Atherosclerotic Stenosis.
    X. Leng, F. Scalzo, A. Fong, M. Johnson, H. Ip, Y. Soo, T. Leung, L. Liu, E. Feldmann, K. Wong, D. Liebeskind. Neurovascular Imaging. in press, 2014.

  197. CFD Modeling of Symptomatic Intracranial Atherosclerosis May Predict Risk of Stroke Recurrence.
    X. Leng, F. Scalzo, H. Ip, M. Johnson, A. Fong, F. Fan, X. Chen, Y. Soo, Z. Miao, L. Liu, E. Feldmann, T. Leung, D. Liebeskind, K. Wong. Plos One. in press, 2014.

  198. Pediatric Heart Sound Segmentation Using Hidden Markov Model
    P. Sedighian, A. Subudhi, F. Scalzo, S. Asgari. EMBC, 2014.
  199. STAR: CT and MR Perfusion Imaging and Good Outcomes in Endovascular Stroke Treatment.
    D. Liebeskind, F. Scalzo, et al. International Stroke Conference (ISC), 2014 (Abstract).
  200. A 3D Computational Model of the Hemodynamic Changes in EC-IC Bypass With Physiologic Boundary Conditions.
    M. Connolly, F. Scalzo, et al. International Stroke Conference (ISC), 2014 (Abstract).
  201. Excellent Collaterals in STAR: Minimal Infarct Core Trumps the Degree of Hypoperfusion.
    D. Liebeskind, F. Scalzo, et al. International Stroke Conference (ISC), 2014 (Abstract).
  202. Arterial-Spin Labeled MRI After Endovascular Stroke Therapy: Validation of a Novel Scale to Quantify the Degree and Heterogeneity of Reperfusion.
    D. Liebeskind, et al. International Stroke Conference (ISC), 2014 (Abstract).
  203. Collateral Grade on MRI - Validation With Conventional Angiography is Key.
    K. Ng, et al. International Stroke Conference (ISC), 2014 (Abstract).
  204. Early Reperfusion with a Stentriever Device: A First Step to Superior Outcomes in TREVO2.
    D. Liebeskind, F. Scalzo, et al. International Stroke Conference (ISC), 2014 (Abstract).
  205. MRI Voxel-Based Profiling of Tissue Viability and Ischemia in Acute Ischemic Stroke: Elimination of Time as a Treatment Barrier?
    A. Tansy, F. Scalzo, et al. International Stroke Conference (ISC), 2014 (Abstract).
  206. CT Angiography of Symptomatic Intracranial Atherosclerosis: Anatomical Predictors of Fractional Flow.
    D. Liebeskind, et al. International Stroke Conference (ISC), 2014 (Abstract).
  207. Computational Flow Model of Intracranial Arterial Stenosis With Physiologic Boundary Conditions.
    M. Connolly, F. Scalzo, et al. International Stroke Conference (ISC), 2014 (Abstract).
  208. Collaterals, Not Clots! CT Angiography Predictors of Recanalization, Reperfusion and Clinical Outcomes After Thrombectomy in Pooled Analyses of TREVO EU and TREVO2.
    D. Liebeskind, et al. International Stroke Conference (ISC), 2014 (Abstract).
  209. Angiographic Arteriovenous Shunting in Large Vessel Occlusion Strokes: Not an Ominous Sign.
    R. Nogueira, et al. International Stroke Conference (ISC), 2014 (Abstract).
  210. PerfAngio: A Software Solution for Quantitative Perfusion Angiography
    F. Scalzo et al. International Stroke Conference (ISC), 2014 (Abstract).
  211. Serial Analysis of Perfusion Angiography in Endovascular Intervention for Acute Stroke With Proximal Middle Cerebral Artery Occlusion.
    J. Tarpley, F. Scalzo, et al. International Stroke Conference (ISC), 2014 (Abstract).

  212. 2013

  213. Noninvasive fractional flow on MRA predicts stroke risk of intracranial stenosis in SONIA/WASID.
    D. Liebeskind, A. Kosinski, M. Lynn, F. Scalzo, A. Fong, P. Fariborz. Stroke. 44, 2013.

  214. Ensemble of Sparse Classifiers for High-Dimensional Biological Data.
    S. Kim, F. Scalzo, D. Telesca, X. Hu. IJDMB. in press, 2013.

  215. The combination of baseline MR-PWI tissue volume with severely prolonged arterial-tissue delay and DWI lesion volume is predictive of MCA-M1 recanalization in patients treated with endovascular thrombectomy.
    F. Nicoli, F. Scalzo, J. L. Saver, F. Pautot, A. Mitulescu, Y. Chaibi, N. Girard, N. Salamon, D. S. Liebeskind. Neuroradiology, 2013.

  216. Ischemia-Reperfusion Injury in Stroke.
    M. Nour, F. Scalzo, D. Liebeskind. Interventional Neurology. vol 1, No 3-4, 2013.

  217. Multi-Center Prediction of Hemorrhagic Transformation in Acute Ischemic Stroke using Permeability Imaging Features. F. Scalzo, J. Alger, X. Hu, J. Saver, K. Dani, K. Muir, A. Demchuk, S. Coutts, M. Luby, S. Warach, D. Liebeskind. Magn Reson Imaging. 1(6):961-9, 2013.

  218. Semi-Supervised Detection of Intracranial Pressure Alarms using Waveform Dynamics.
    F. Scalzo, X. Hu. Physiol. Meas. 34, 465-478. 2013.
  219. Development of a 3-Dimensional Computational Blood Flow Model of Intracranial Arterial Stenosis.
    M. Connolly, et al. Congress of Neurological Surgeons (CNS), 2013 (Abstract).
  220. A 3-Dimensional Flow Analysis of a Computational Extracranial-Intracranial Bypass Model.
    M. Connolly, et al. Congress of Neurological Surgeons (CNS), 2013 (Abstract).
  221. High-resolution mapping of the collateral circulation deficit in patients with acute MCA-M1 occlusion by Bayesian processing of MR PWI. F. Nicoli, et al. European Stroke Conference, 2013 (Abstract).
  222. SAMMPRIS Angiography Discloses Hemodynamic Effects of Intracranial Stenosis: CFD of Fractional Flow.
    D. Liebeskind, et al. ISC, 2013 (Abstract).
  223. Perfusion Angiography in TREVO2: Quantitative Reperfusion After Endovascular Therapy in Acute Stroke.
    D. Liebeskind, et al. ISC, 2013 (Abstract).
  224. Early DWI Changes in the Thrombolysis Time Window: From DWI-Negative to Malignant Stroke in More than 300 Cases.
    D. Liebeskind, et al. ISC, 2013 (Abstract).
  225. Reperfusion? Angiography and Serial Perfusion MRI Reveal Distinct Features of Endovascular Therapy for Middle Cerebral Artery Stroke.
    D. Liebeskind, et al. ISC, 2013 (Abstract).
  226. Arterial Spin-Labeled Perfusion MRI with Multi-Delay: Expanding Beyond CBF in Acute Ischemic Stroke.
    D. Liebeskind, et al. ISC, 2013 (Abstract).
  227. Insight Into Human Ischemia Reperfusion Injury in Acute Stroke: A Voxel- Based MRI Analysis of Tissue Fate.
    D. Liebeskind, et al. ISC, 2013 (Abstract).
  228. Noninvasive Fractional Flow on MRA Predicts Stroke Risk of Intracranial Stenosis in SONIA/WASID.
    D. Liebeskind, et al. ISC, 2013 (Abstract).

  229. 2012

  230. Reducing False Intracranial Pressure Alarms using Morphological Waveform Features.
    F. Scalzo, D. Liebeskind, and X. Hu. IEEE Trans Biomed Eng. July, 2012. (Letters, ~17% acceptance rate)
  231. Regional Prediction of Tissue Fate in Acute Ischemic Stroke.
    F. Scalzo, Q. Hao, J. Alger, X. Hu, and D. Liebeskind. Annals of Biomedical Engineering. May, 2012.
  232. Intracranial Pressure Signal Morphology: real-time tracking.
    F. Scalzo, M. Bergsneider, P. Vespa, N. Martin, and X. Hu. IEEE pulse. 3(2):49-52. 2012.
  233. Intracranial Hypertension Prediction using Extremely Randomized Decision Trees.
    F. Scalzo, R. Hamilton, S. Asgari, S. Kim, and X. Hu. Med Eng Phys. March, 2012.
  234. Reperfusion Injury in Acute Ischemic Stroke: Voxel-based Analysis of Tissue Fate Using Serial MRI.
    M. Nour, F. Scalzo, D. Liebeskind. UCLA Collins Day 2012. Best Poster Award.
  235. Perfusion Augmentation with the NeuroFlo Device in the SENTIS Trial: Cerebral Blood Volume Gradients Improve on Serial MRI. D. Liebeskind, et al. International Stroke Conference 2012 (Abstract).
  236. Multiparametric T2*-Permeability MRI Accurately Predicts Hemorrhagic Transformation: STIR/VISTA Imaging Multicenter Observational Study. D. Liebeskind, et al. International Stroke Conference 2012 (Abstract).

  237. 2011

  238. Bayesian Tracking of Intracranial Pressure Signal Morphology.
    F. Scalzo, S. Asgari, S. Kim, M. Bergsneider, and X. Hu. Artif Intell Med, October, 2011. Best Poster Award at ICP 2010.

  239. Noninvasive Intracranial Hypertension Diagnosis using Ensemble Sparse Classifiers.
    S. Kim, F. Scalzo, X. Hu. KDD Workshop: 17th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2011. (Poster)
  240. Automatic Prediction of Intracranial Hypertension Using Decision Trees.
    F. Scalzo, R. Hamilton, S. Asgari, S. Kim, X. Hu. 14th European Congress of Neurosurgery (EANS), 2011. (Oral)
  241. Impact of Ventriculoperitoneal shunt on CSF dynamics within Normal Pressure Hydrocephalus population: a phase contrast MRI Study.
    R. Hamilton et al. 14th European Congress of Neurosurgery (EANS), 2011. (Poster)
  242. CT Findings at the Earliest Stages of Ischemia: Imaging from the FAST-MAG Prehospital Stroke Trial.
    D. Liebeskind et al. International Stroke Conference 2011 (Oral).
  243. Subacute Infarct Extension and Topography of MCA Stroke Reflects Collateral Failure: A 3D Atlas for Collateral Therapeutics.
    D. Liebeskind, F. Scalzo, N. Sanossian, Q. Hao, X. Hu. International Stroke Conference 2011 (Oral).
  244. Cerebral Blood Volume Gradient Maps Depict Vulnerability to Hemodynamic Failure and Infarct Growth in Acute Ischemic Stroke.
    D. Liebeskind, F. Scalzo, Q. Hao, J. Alger, X. Hu. International Stroke Conference 2011 (Poster).
  245. 2D-3D Computational Fluid Dynamics Add Novel Dimension to Recanalization Scores in Acute Middle Cerebral Artery Occlusion.
    D. Liebeskind, F. Scalzo, Q. Hao, Y. Hoi, K. Hoffmann, X. Hu. International Stroke Conference 2011 (Poster).
  246. A Regional Model of Collateral Perfusion Accurately Predicts Tissue Fate in Acute Ischemic Stroke.
    D. Liebeskind, F. Scalzo, Q. Hao, J. Alger, X. Hu. International Stroke Conference 2011 (Poster).

  247. 2010

  248. Reducing backward masking through action game training.
    R. Li, U. Polat, F. Scalzo, and D. Bavelier. Journal of Vision, 10(14):33, December, 2010.
  249. Noninvasive Intracranial Pressure Assessment based on Data Mining Approach using Nonlinear Mapping Function.
    S. Kim, F. Scalzo, M. Bergsneider, P. Vespa, N. Martin, and X. Hu. IEEE Trans Biomed Eng, November, 2010.
  250. Robust Peak Recognition in Intracranial Pressure Signals.
    F. Scalzo, S. Asgari, S. Kim, M. Bergsneider, and X. Hu. BioMedical Engineering OnLine, 9:61, October, 2010.
  251. Computational Fuild Dynamics in Intracranial Vessels from Biplane Angiograms.
    F. Scalzo, Q. Hao, A. Walczak, X. Hu, Y. Hoi, K. Hoffmann, D. Liebeskind. Defense Advanced Research Projects Agency (DARPA) NEST Forum, 2010 (Poster).
  252. Data Mining Approach-Based Noninvasive Intracranial Pressure Monitoring.
    S. Kim, F. Scalzo, M. Bergsneider, X. Hu. Defense Advanced Research Projects Agency (DARPA) NEST Forum, 2010.
  253. Real-time Tracking of Intracranial Pressure Signal Morphology using Bayesian Inference.
    F. Scalzo, R. Hamilton, S. Kim, S. Asgari, M. Bergsneider, X. Hu.
    International Conference on Intracranial Pressure and Brain Monitoring, 2010. Best Poster Award.
    Defense Advanced Research Projects Agency (DARPA) NEST Forum, 2010.
  254. Feature-based Peak Recognition in Challenging Intracranial Pressure Signals.
    F. Scalzo, S. Asgari, S. Kim, M. Bergsneider, X. Hu. International Conference on Intracranial Pressure and Brain Monitoring, 2010.
  255. Tissue Fate Prediction in Acute Ischemic Stroke using Cuboid Models.
    F. Scalzo, Q. Hao, J. Alger, X. Hu, D. Liebeskind. International Symposium on Visual Computing, 2010.
  256. Computational Hemodynamics in Intracranial Vessels Reconstructed from Biplane Angiograms.
    F. Scalzo, Q. Hao, A. Walczak, X. Hu, Y. Hoi, K. Hoffmann, D. Liebeskind. International Symposium on Visual Computing, 2010.
  257. Noninvasive Intracranial Hypertension Detection based on Cerebral Blood Flow Velocity Waveform Alone.
    S. Kim, F. Scalzo, M. Bergsneider, P. Vespa, X. Hu. International Conference on Complexity in Acute Illness, 2010.
  258. Computational Fluid Dynamics of Retrograde Leptomeningeal Collateral Flow in Acute Ischemic Stroke: Unique Insight on Essential Hemodynamics.
    D. Liebeskind, F. Scalzo, Y. Hoi, X. Hu, D. Steinman. American Academy of Neurology Annual Meeting, 2010.
  259. Intracranial Pressure Pulse Morphological Features Improved Detection of Decreased Cerebral Blood Flow.
    X. Hu, T. Glenn, F. Scalzo, M. Bergsneider, C. Sarkiss, N. Martin, P. Vespa. Physiological Measurement, 31:679, April, 2010.

  260. 2009

  261. Regression Analysis for Peak Designation in Pulsatile Pressure Signals.
    F. Scalzo, P. Xu, S. Asgari, M. Bergsneider, X. Hu. Med Biol Eng Comp, 47(9): 967–977, September, 2009.
  262. Morphological Clustering and Analysis of Continuous Intracranial Pressure.
    X. Hu, P. Xu, F. Scalzo, P. Vespa, M. Bergsneider. IEEE Trans Biomed Eng, 56(3):696-705, March, 2009.
  263. Unsupervised Learning of Generative Factor Graph Hierarchies.
    F. Scalzo. ICML Workshop on Learning Feature Hierarchies, 2009. Spotlight presentation.


  264. 2008

  265. Random Subwindows for Robust Peak Recognition in Intracranial Pressure Signals.
    F. Scalzo, P. Xu, M. Bergsneider, X. Hu. International Symposium on Visual Computing (ISVC), Lecture Notes in Computer Science, 5358:370-380, 2008. (Oral)
  266. Predicting Cerebral Blood Flow Based on a Multimodal Approach.
    C. Sarkiss, F. Scalzo, T. Glenn, N. Martin, X. Hu. UCLA Josiah Brown Poster Fair 2008.
  267. Nonlinear Regression For Sub-Peak Detection of Intracranial Pressure Signals.
    F. Scalzo, P. Xu, M. Bergsneider, X. Hu. IEEE Int. Conf. Engineering and Biology Society (EMBC), 5411-5414, 2008. (Oral)
  268. Wavelet Entropy Characterization of Elevated Intracranial Pressure.
    P. Xu, F. Scalzo, M. Bergsneider, X. Hu. IEEE Int. Conf. Engineering and Biology Society (EMBC), 2924-2927, 2008.
  269. Feature Fusion Hierarchies for Gender Classification.
    F. Scalzo, G. Bebis, M. Nicolescu, L. Loss, A. Tavakkoli. Proc. of the International Conference on Pattern Recognition (ICPR), 2008.
  270. Hierarchical Markov Network for Object Recognition.
    J. Piater, F. Scalzo, and R. Detry. Proc. of the Annual Machine Learning Conference of Belgium and the Netherlands (Benelearn), 1:65-66, 2008.
  271. Morphological Feature Extraction of Intracranial Pressure Signals via Nonlinear Regression.
    F. Scalzo, P. Xu, M. Bergsneider, X. Hu. Proc. of the Annual Machine Learning Conference of Belgium and the Netherlands (Benelearn), 1:87-88, 2008.
  272. Evolutionary Learning of Feature Fusion Hierarchies.
    F. Scalzo, G. Bebis, M. Nicolescu, L. Loss. Proc. of the Annual Machine Learning Conference of Belgium and the Netherlands (Benelearn), 1:33-34, 2008.
  273. Vision as Inference in a Hierarchical Markov Network.
    J. Piater, F. Scalzo, and R. Detry. International Conference on Cognitive and Neural Systems (ICCNS), 2008.

  274. 2007 and earlier

  275. Adaptive patch features for object class recognition with learned hierarchical models.
    F. Scalzo, J. Piater. Proc. of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2007.
  276. Unsupervised Learning of Dense Hierarchical Appearance Representations.
    F. Scalzo, J. Piater. Proc. of the International Conference on Pattern Recognition (ICPR), 2:395-398, 2006.
  277. Combining Generative and Discriminative Learning of Feature Hierarchies for Object Recognition.
    F. Scalzo, J. Piater. Research Contact Day of the CIL doctoral school, 2006.
  278. Statistical learning of visual feature hierarchies.
    F. Scalzo, J. Piater. Proc. of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2005.
  279. Task-Driven Learning of Spatial Combinations of Visual Features.
    S. Jodogne, F. Scalzo, J. Piater. Proc. of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2005.
  280. Unsupervised Learning of Visual Feature Hierarchies.
    F. Scalzo, J. Piater. Proc. of the International Conference on Machine Learning and Data Mining (MLDM), Lecture Notes in Computer Science, 3587:243-252, 2005.
  281. Apprentissage Non-Supervise de Caracteristiques Visuelles.
    F. Scalzo, J. Piater. Congres des jeunes chercheurs en vision par ordinateur (ORASIS). (Fournol, France), 2005.


Book Chapters & Books

Learning Visual Feature Hierarchies.
F. Scalzo. VDM Verlag, ISBN 978-3-639-18002-2, July, 2009.

Real-time analysis of intracranial pressure waveform morphology.
F. Scalzo, R. Hamilton, and X. Hu. Neurological Disorders: InTech, 2012.


Thesis

Learning Visual Feature Hierarchies.
F. Scalzo. PhD Thesis. University of Liege, Belgium. 2007-2008.