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2017
  1. Explainable Artificial Intelligence Model of Noninvasive Intracranial Pressure.
    F. Scalzo, R. Hamilton. ISS R&D, 2017.
  2. 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.
  3. Low-complexity Tracking of Neurological State using Manifold Learning.
    A. Rajagopal, S. Chandrasekaran, F. Scalzo. UC bioengineering symposium, 2017. Best Poster Award.
  4. 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.
  5. 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.
  6. 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.
  7. Morphologic Changes in ICP Waveform Demonstrate Compliance Changes Irrespective of Intracranial Hypertension.
    M. Brown, W. Baker, F. Scalzo, A. Kofke. NACCSGBI, 2017.
  8. 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.
  9. Longitudinal Recovery of Cerebrovascular Impairment Following Sports Related Concussion Utilizing TCD.
    C. Thibeault et al. AAN, 2017.
  10. ASPECTS Based Reperfusion Status on ASL is Associated with Clinical Outcome in Acute Ischemic Stroke Patients.
    S. Yu et al. JCBFM, 2017.
  11. 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%)
  12. Multi-Delay ASL Can Identify Leptomeningeal Collateral Perfusion in Endovascular Therapy of Ischemic Stroke.
    X. Lou et al. Oncotarget, 2017.
  13. 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.
  14. 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.
  15. 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.
  16. 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.
  17. A Novel Collateral Metric of MCA Hemodynamics in SAMMPRIS.
    D. Liebeskind et al. ISC, 2017.
  18. CTA Collateral Gradient Mapping: Validation of a Novel Imaging Technique in Acute Ischemic Stroke.
    D. Liebeskind et al. ISC, 2017.
  19. Imaging Clot Porosity Prior to Endovascular Thrombectomy.
    D. Liebeskind et al. ISC, 2017.
  20. Collaterals and Reperfusion Mediate Blood Pressure Changes in Acute Ischemic Stroke.
    D. Liebeskind et al. ISC, 2017.
  21. 2016

  22. Perfusion Angiography in Acute Ischemic Stroke.
    F. Scalzo, D. Liebeskind. Comput Math Methods Med, 2016.
  23. Same Decision Probability in Neurocritical Care.
    F. Scalzo, A. Choi, A. Darwiche. Machine Learning for Healthcare, 2016.
  24. Extraction of Vascular Intensity Gradient on Computed Tomography Angiography.
    E. Agbayani, B. Jia, G. Woolf, D. Liebeskind, F. Scalzo. ISVC, 2016.
  25. Similarity Metric Learning for 2D to 3D Registration of Brain Vasculature.
    A. Tang, F. Scalzo. ISVC, 2016.
  26. Tensor Voting Extraction of Vessel Centerlines from Cerebral Angiograms.
    Y. Ding, M. Nicolescu, D. Farmer, Y. Wang, G. Bebis, F. Scalzo. ISVC, 2016.
  27. Vessel Detection on Cerebral Angiograms using Convolutional Neural Networks.
    Y. Fu, J. Fang, B. Quachtran, N. Chachkhiani, F. Scalzo. ISVC, 2016.
  28. 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.
  29. 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.
  30. Detection of Intracranial Hypertension using Deep Learning.
    B. Quachtran, R. Hamilton, F. Scalzo. ICPR, 2016.
  31. 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.
  32. 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.
  33. 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.
  34. Normative Ranges of Transcranial Doppler Metrics.
    C. Thibeault, J. LaVangie, M. O'Brien, A. Sarraf, S. Wilk, F. Scalzo, R. Hamilton. ICP 2016.
  35. Noninvasive Intracranial Pressure Monitoring with Manifold-based Waveform Reconstruction.
    F. Scalzo, R. Hamilton, N. Gonzalez, P. Vespa, X. Hu. ICP 2016.
  36. 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.
  37. Noise Reduction in Intracranial Pressure Signal using Causal Shape Manifolds.
    A. Rajagopal, R. Hamilton, F. Scalzo. Biomedical Signal Processing and Control 2016.
  38. 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.
  39. Deep Learning of MR Imaging Patterns in Prostate Cancer.
    N. Tan, N. Stier, N. Asvadi, A. Moshksar, S. Raman, F. Scalzo. ISMRM 2016.
  40. Detection of Prostate Cancer from Multi-parametric Regional MRI Features.
    N. Tan, A. Moshksar, N. Asvadi, S. Raman, F. Scalzo. ISMRM 2016.
  41. 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.
  42. Probabilistic Labeling of Cerebral Vasculature on MR Angiography.
    B. Quachtran, S. Sheth, J. Saver, D. Liebeskind, F. Scalzo. LNCS 2016.
  43. 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.
  44. Hyperperfusion on Arterial Spin Labeling: Objective Decision Support using Pattern Recognition.
    F. Scalzo, S. Yu, S. Patel, D. Liebeskind, D. JJ Wang. ISC 2016.
  45. 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.
  46. Automated Labeling of Cerebral Vasculature on MR Angiography Using Nonparametric Bayesian Inference.
    B. Quachtran, S. Sheth, J. Saver, D. Liebeskind, F. Scalzo. ISC 2016.
  47. 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.
  48. 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.
  49. 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.
  50. 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.
  51. 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.
  52. Detection of Prostate Cancer based on Multi-parametric Regional MRI Features.
    N. Tan, A. Moshksar, S. Raman, F. Scalzo. SIIM 2016.
  53. 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.
  54. 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.
  55. 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.

  56. 2015

  57. Deep Learning of Tissue Fate Features in Acute Ischemic Stroke.
    N. Stier, N. Vincent. D. Liebeskind, F. Scalzo. IEEE BIBM. 2015.
  58. 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.
  59. 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
  60. 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.
  61. Data Science of Stroke Imaging and Enlightenment of the Penumbra.
    F. Scalzo, M. Nour, D. Liebeskind. Frontiers in Neurology (Stroke), in press, 2015.

  62. Time for Collaterals? Evidence from 695 Endovascular Therapy Cases for Acute Stroke in ENDOSTROKE.
    D. Liebeskind, et al. ISC 2015.
  63. Probabilistic Atlasing of Acute Ischemic Stroke Topology.
    D. Ichwan, F. Scalzo, D. Liu, B. Bergsneider, A. Anderson, D. Liebeskind. ISC, 2015.
  64. Classification of DWI Lesion Patterns in Acute Ischemic Stroke using Shape Context.
    F. Scalzo, D. Liu, D. Liebeskind. ISC, 2015.
  65. Predicting Omni-directional Lesion growth in Acute Stroke using Multimodal Intensity Profiles.
    F. Scalzo, W. Chowdhury, D. Liebeskind. ISC, 2015.
  66. FACET: Fractal Angiography for Continuous Revascularization Evaluation during Thrombectomy.
    F. Scalzo, C. Thorenfeldt, S. Sheth, C. Liang, G. Duckwiler, D. Liebeskind. ISC, 2015.
  67. Coregistration of Serial Angiograms using Point Cloud Matching.
    F. Scalzo, N. Stier, J. Liu, W. Bi, D. Liebeskind. ISC, 2015.
  68. Cerebral Oxygen Extraction Fraction MRI to Assess Metabolic Changes in Acute Ischemic Stroke.
    L. Sharma et al. ISC, 2015.
  69. 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.
  70. Different Strokes: Causality and Outcomes in the NINDS-tPA Trials.
    D. Liebeskind, A. Choi, N. Sanossian, S. Fang, A. Darwiche, F. Scalzo. ISC, 2015.
  71. 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.
  72. 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.
  73. 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.
  74. 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.
  75. 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.
  76. 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.
  77. 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.
  78. 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.
  79. 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.
  80. 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.
  81. Time for Collaterals? Evidence from 695 Endovascular Therapy Cases for Acute Stroke in ENDOSTROKE.
    D. Liebeskind, et al. ISC, 2015.
  82. 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.
  83. 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.
  84. 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.

  85. 2014

  86. 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.

  87. 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.

  88. Pediatric Heart Sound Segmentation Using Hidden Markov Model
    P. Sedighian, A. Subudhi, F. Scalzo, S. Asgari. EMBC, 2014.
  89. 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).
  90. 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).
  91. Excellent Collaterals in STAR: Minimal Infarct Core Trumps the Degree of Hypoperfusion.
    D. Liebeskind, F. Scalzo, et al. International Stroke Conference (ISC), 2014 (Abstract).
  92. 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).
  93. Collateral Grade on MRI - Validation With Conventional Angiography is Key.
    K. Ng, et al. International Stroke Conference (ISC), 2014 (Abstract).
  94. 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).
  95. 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).
  96. CT Angiography of Symptomatic Intracranial Atherosclerosis: Anatomical Predictors of Fractional Flow.
    D. Liebeskind, et al. International Stroke Conference (ISC), 2014 (Abstract).
  97. Computational Flow Model of Intracranial Arterial Stenosis With Physiologic Boundary Conditions.
    M. Connolly, F. Scalzo, et al. International Stroke Conference (ISC), 2014 (Abstract).
  98. 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).
  99. Angiographic Arteriovenous Shunting in Large Vessel Occlusion Strokes: Not an Ominous Sign.
    R. Nogueira, et al. International Stroke Conference (ISC), 2014 (Abstract).
  100. PerfAngio: A Software Solution for Quantitative Perfusion Angiography
    F. Scalzo et al. International Stroke Conference (ISC), 2014 (Abstract).
  101. 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).

  102. 2013

  103. 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.

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

  105. 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.

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

  107. 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.

  108. Semi-Supervised Detection of Intracranial Pressure Alarms using Waveform Dynamics.
    F. Scalzo, X. Hu. Physiol. Meas. 34, 465-478. 2013.
  109. Development of a 3-Dimensional Computational Blood Flow Model of Intracranial Arterial Stenosis.
    M. Connolly, et al. Congress of Neurological Surgeons (CNS), 2013 (Abstract).
  110. A 3-Dimensional Flow Analysis of a Computational Extracranial-Intracranial Bypass Model.
    M. Connolly, et al. Congress of Neurological Surgeons (CNS), 2013 (Abstract).
  111. 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).
  112. SAMMPRIS Angiography Discloses Hemodynamic Effects of Intracranial Stenosis: CFD of Fractional Flow.
    D. Liebeskind, et al. ISC, 2013 (Abstract).
  113. Perfusion Angiography in TREVO2: Quantitative Reperfusion After Endovascular Therapy in Acute Stroke.
    D. Liebeskind, et al. ISC, 2013 (Abstract).
  114. 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).
  115. Reperfusion? Angiography and Serial Perfusion MRI Reveal Distinct Features of Endovascular Therapy for Middle Cerebral Artery Stroke.
    D. Liebeskind, et al. ISC, 2013 (Abstract).
  116. Arterial Spin-Labeled Perfusion MRI with Multi-Delay: Expanding Beyond CBF in Acute Ischemic Stroke.
    D. Liebeskind, et al. ISC, 2013 (Abstract).
  117. Insight Into Human Ischemia Reperfusion Injury in Acute Stroke: A Voxel- Based MRI Analysis of Tissue Fate.
    D. Liebeskind, et al. ISC, 2013 (Abstract).
  118. Noninvasive Fractional Flow on MRA Predicts Stroke Risk of Intracranial Stenosis in SONIA/WASID.
    D. Liebeskind, et al. ISC, 2013 (Abstract).

  119. 2012

  120. 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)
  121. 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.
  122. 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.
  123. Intracranial Hypertension Prediction using Extremely Randomized Decision Trees.
    F. Scalzo, R. Hamilton, S. Asgari, S. Kim, and X. Hu. Med Eng Phys. March, 2012.
  124. 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.
  125. 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).
  126. Multiparametric T2*-Permeability MRI Accurately Predicts Hemorrhagic Transformation: STIR/VISTA Imaging Multicenter Observational Study. D. Liebeskind, et al. International Stroke Conference 2012 (Abstract).

  127. 2011

  128. 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.

  129. 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)
  130. 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)
  131. 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)
  132. 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).
  133. 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).
  134. 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).
  135. 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).
  136. 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).

  137. 2010

  138. Reducing backward masking through action game training.
    R. Li, U. Polat, F. Scalzo, and D. Bavelier. Journal of Vision, 10(14):33, December, 2010.
  139. 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.
  140. 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.
  141. 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).
  142. 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.
  143. 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.
  144. 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.
  145. 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.
  146. 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.
  147. 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.
  148. 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.
  149. 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.

  150. 2009

  151. 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.
  152. 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.
  153. Unsupervised Learning of Generative Factor Graph Hierarchies.
    F. Scalzo. ICML Workshop on Learning Feature Hierarchies, 2009. Spotlight presentation.


  154. 2008

  155. 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)
  156. 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.
  157. 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)
  158. 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.
  159. 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.
  160. 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.
  161. 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.
  162. 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.
  163. Vision as Inference in a Hierarchical Markov Network.
    J. Piater, F. Scalzo, and R. Detry. International Conference on Cognitive and Neural Systems (ICCNS), 2008.

  164. 2007 and earlier

  165. 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.
  166. Unsupervised Learning of Dense Hierarchical Appearance Representations.
    F. Scalzo, J. Piater. Proc. of the International Conference on Pattern Recognition (ICPR), 2:395-398, 2006.
  167. Combining Generative and Discriminative Learning of Feature Hierarchies for Object Recognition.
    F. Scalzo, J. Piater. Research Contact Day of the CIL doctoral school, 2006.
  168. Statistical learning of visual feature hierarchies.
    F. Scalzo, J. Piater. Proc. of the IEEE Workshop on Learning in Computer Vision and Pattern Recognition (CVPR), 2005.
  169. Task-Driven Learning of Spatial Combinations of Visual Features.
    S. Jodogne, F. Scalzo, J. Piater. Proc. of the IEEE Workshop on Learning in Computer Vision and Pattern Recognition (CVPR), 2005.
  170. 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.
  171. 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.