Perelman School of Medicine at the University of Pennsylvania

Section for Biomedical Image Analysis (SBIA)

participating with CBICA

Spyridon (Spyros) Bakas, Ph.D.


Postdoctoral Researcher

Section of Biomedical Image Analysis
Center for Biomedical Image Computing & Analytics
Department of Radiology
Perelman School of Medicine
University of Pennsylvania

Richards Medical Research Laboratories, Floor 7
3700 Hamilton Walk
Philadelphia, PA 19104
fax: (001) 215.573.1811
email: S.Bakas@uphs.upenn.edu

News

- Cancer Cell: New publication on EGFR ECD mutations in GBM presenting opportunities for therapeutic development.(09 Jul'18)
- SNO 2018: I have been invited to moderate the Neuro-Imaging session in the Society for Neuro-Oncology Meeting, on Nov15.
- SNO 2018: I am organizing the 'Computational Neuro-Oncology' session in the Society for Neuro-Oncology Meeting, on Nov17.
- Neuro-Oncology: New publication on in vivo evaluation of EGFRvIII in glioblastoma via multiparametric MRI. (30 Mar'18)
- MICCAI 2018: I am leading the organisation of the International Brain Tumor Segmentation (BraTS) challenge 2018, on Sep16.
- MICCAI 2018: I am co-organizing the Full-day MICCAI workshop on Brain Lesions (BrainLes) 2018, on Sep16.
- MICCAI 2018: I am co-organizing the Workshop and Challenges in Computational Precision Medicine, on Sep16.
- MICCAI 2018: I am organizing the Full-day tutorial on Tools Allowing Clinical Translation of Image Computing ALgorithms (TACTICAL) 2018, on Sep20.
- MICCAI 2018: I am involved in the organization of the Medical Segmentation Decathlon challenge, on Sep20.
- ISBI 2018: I am co-organizing the half-day hands-on Tutorial on the Cancer Imaging Phenomics Toolkit (CaPTk).
- JAMA Pediatrics: Our work on predicting the need for intervention in fetal ventriculomegaly initiated an Editorial. (Feb'17)

Educational Qualifications

Ph.D. in Medical Image Computing & Analysis - Kingston University, London (UK)
M.Sc. in Vision, Imaging & Virtual Environments - University College London (UK)
B.Sc. (Hons) in Computer Science - Kingston University, London (UK)

Research Summary

My research interest focuses on the development and application of computational algorithms in oncological imaging, with the intention of improving the assessment, quantification and diagnosis of cancer in the current clinical practice. Eagerly embracing the concept of personalized/precision medicine, I am also involved in radiogenomic research where correlations between quantitative imaging features and genomic information lead to highly accurate imaging biomarkers, which can enable treatment selection models customized on an individual patient basis. My work so far has spanned across the areas of image segmentation, feature extraction, statistical analysis, motion analysis and machine learning techniques applied in brain magnetic-resonance (MR), and liver contrast-enhanced ultrasound (CEUS), imaging data. The ultimate aim of my research is to contribute towards making diagnostic and treatment decisions more promptly, objectively, and precisely.

Published Material

Journals

  1. Zev A. Binder, Amy Haseley Thorne, Spyridon Bakas, E. Paul Wileyto, Michel Bilello, Hamed Akbari, Saima Rathore, Sung Min Ha, Logan Zhang, Cole J. Ferguson, Sonika Dahiya, Wenya Linda Bi, David A. Reardon, Ahmed Idbaih, Joerg Felsberg, Bettina Hentschel, Michael Weller, Stephen J. Bagley, Jennifer J.D. Morrissette, MacLean P. Nasrallah, Jianhui Ma, Ciro Zanca, Andrew M. Scott, Laura Orellana, Christos Davatzikos, Frank B. Furnari, Donald M. O’Rourke, "Epidermal Growth Factor Receptor Extracellular Domain Mutations in Glioblastoma Present Opportunities for Clinical Imaging and Therapeutic Development", Cancer Cell, 34:163-177, 2018. DOI: 10.1016/j.ccell.2018.06.006
  2. Xu Han, Roland Kwitt, Stephen Aylward, Spyridon Bakas, Bjoern Menze, Alexander Asturias, Paul Vespa, John Van Horn, Marc Niethammer, "Brain Extraction from Normal and Pathological Images: A Joint PCA/Image-Reconstruction Approach", Neuro-Image, [In Press], 2018
  3. Hamed Akbari, Spyridon Bakas, Jared Pisapia, MacLean P Nasrallah, Martin Rozycki, Maria Martinez-Lage, Jennifer J D Morrissette, Nadia Dahmane, Donald M O’RourkeChristos Davatzikos. "In vivo evaluation of EGFRvIII mutation in primary glioblastoma patients via complex multi-parametric MRI signature", Neuro Oncology, [In Press], March 30 2018. DOI: 10.1093/neuonc/noy033
  4. Jared M. Pisapia, Hamed Akbari, Martin Rozycki, Hannah Goldstein, Spyridon Bakas, Saima Rathore, Julie S. Moldenhauer, Phillip B. Storm, Deborah M. Zarnow, Richard C.E. Anderson, Gregory G. Heuer, Christos Davatzikos, “Predicting Need for Post-Natal Cerebrospinal Fluid Diversion in Fetal Ventriculomegaly using Fetal Magnetic Resonance Image Analysis and Machine Learning”, JAMA Pediatrics, 172(2):128-135, 2018. DOI: 10.1001/jamapediatrics.2017.3993
  5. Gaurav Shukla, Gregory S Alexander, Spyridon Bakas, Rahul Nikam, Kiran Talekar, Joshua D. Palmer, Wenyin Shi, "Advanced Magnetic Resonance Imaging in Glioblastoma: A Review", JHN Journal, 13(1):30-34, 2018. DOI: 10.29046/JHNJ.013.1.005
  6. Christos Davatzikos, Saima Rathore, Spyridon Bakas, Sarthak Pati, Mark Bergman, Ratheesh Kalarot, Patmaa Sridharan, Aimilia Gastounioti, Nariman Jahani, Erik Cohen, Hamed Akbari, Birkan Tunc, Jimit Doshi, Drew Parker, Michael Hsieh, Aristeidis Sotiras, Hongming Li, Yangming Ou, R.K.Doot, Michel Bilello, Yong Fan, Russell T. Shinohara, Paul Yushkevich, Ragini Verma, Despina Kontos, “Cancer Imaging Phenomics Toolkit: Quantitative Imaging Analytics for Precision Diagnostics and Predictive Modeling of Clinical Outcome”, Journal of Medical Imaging: Special Section on Quantitative Imaging Methods and Translational Developments – Honoring the Memory of Dr. Larry Clarke, 5(1):0110118, 2018. DOI:  10.1117/1.JMI.5.1.011018
  7. Spyridon Bakas, Hamed Akbari, Aristeidis Sotiras, Michel Bilello, Martin Rozycki, Justin S. Kirby, John B. Freymann, Keyvan Farahani, Christos Davatzikos. "Advancing The Cancer Genome Atlas glioma MRI collections with expert segmentation labels and radiomic features", Nature Scientific Data, 4:170117, September 5 2017. DOI: 10.1038/sdata.2017.117
    (Publisher's version)
  8. Spyridon Bakas, Hamed Akbari, Jared Pisapia, Maria Martinez-Lage, Martin Rozycki, Saima Rathore, Nadia Dahmane, Donald M. O’Rourke, Christos Davatzikos. "In vivo detection of EGFRvIII in glioblastoma via perfusion magnetic resonance imaging signature consistent with deep peritumoral infiltration: the φ index", Clin Cancer Research, 23(16):4724-4734, August 15 2017. DOI: 10.1158/1078-0432.CCR-16-1871
    (Publisher's version)
  9. Gaurav Shukla, Gregory S. Alexander, Spyridon Bakas, Rahul Nikam, Kiran Talekar, Joshua D. Palmer, Wenyin Shi, "Advanced magnetic resonance imaging in glioblastoma: a review", Chin Clin Oncol, 6(4):40, August 04 2017. DOI:10.21037/cco.2017.06.28
    (Publisher's version)
  10. Spyridon Bakas, Dimitrios Makris, Gordon J.A. Hunter, Cheng Fang, Paul S. Sidhu, Katerina Chatzimichail. "Automatic Identification of the Optimal Reference Frame for Segmentation and Quantification of Focal Liver Lesions in Contrast-Enhanced Ultrasound", Ultrasound in Medicine & Biology, 43(10):2438–2451, 2017. DOI: 10.1016/j.ultrasmedbio.2017.06.005
  11. Jared M. Pisapia, Martin Rozycki, Hamed AkbariSpyridon Bakas, Jayesh P. Thawani, Julie S. Moldenhauer, Phillip B. Storm, Deborah M. Zarnow, Christos Davatzikos, Gregory G. Heuer. "Correlations of Atrial Diameter and Fronto-Occipital Horn Ratio with Ventricle Size in Fetal Ventriculomegaly", Journal of Neurosurgery: Pediatrics, 19(3):300-306, 2017. DOI: 10.3171/2016.9.PEDS16210
    (Publisher's version)
  12. Spyridon Bakas, Katerina Chatzimichail, Gordon Hunter, Bastien Labbe, Paul S. Sidhu, Dimitrios Makris, "Fast Semi-Automatic Segmentation of Focal Liver Lesions in Contrast-Enhanced Ultrasound, Based on a Probabilistic Model", TCIV Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 5(5):329:338, 2017. DOI: 10.1080/21681163.2015.1029642
    (View Preprint)  —  (Publisher's Version)
  13. Spyridon Bakas, Katerina Chatzimichail, Andreas Hoppe, Vasileios Galariotis, Gordon Hunter, Dimitrios Makris, "Histogram-based Motion Segmentation and Characterisation of Focal Liver Lesions in CEUS", Annals of the BMVA (Special Issue), 2012.
    (Published Version)

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Conferences

  1. Saima Rathore, Spyridon Bakas, Hamed Akbari, Gaurav Shukla, Martin Rozycki, Christos Davatzikos, "Deriving stable multi-parametric MRI radiomic signatures in the presence of inter-scanner variations: survival prediction of glioblastoma via imaging pattern analysis", Medical Imaging 2018:Computer-Aided Diagnosis 10575, 1057509, 2018
  2. Saima Rathore, Spyridon Bakas, Sarthak Pati, Hamed Akbari, Ratheesh Kalarot, Patmaa Sridharan, Martin Rozycki, Mark Bergman, Birkan Tunc, Ragini Verma, Michel Bilello, Christos Davatzikos, “Brain Cancer Imaging Phenomics Toolkit (brain-CaPTk): An Integrative Platform for Quantitative Analysis of Glioblastoma”, Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, Springer, LNCS, 10670:133-145, 2018, DOI: 10.1007/978-3-319-75238-9_12
  3. Ke Zeng, Spyridon Bakas, Aristeidis Sotiras, Hamed Akbari, Martin Rozycki, Saima Rathore, Sarthak Pati, Christos Davatzikos. "Segmentation of Gliomas in Pre-Operative and Post-Operative Multimodal Magnetic Resonance Imaging Volumes Based on a Hybrid Generative-Discriminative Framework", Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, Springer, LNCS, 10154:184-194, 2017. DOI: 10.1007/978-3-319-55524-9_18
    (Athens, Greece, 17-21 Oct 2016)
  4. Ke Zeng, Spyridon Bakas, Aristeidis Sotiras, Hamed Akbari, Martin Rozycki, Saima RathoreSarthak Pati, Christos Davatzikos. "Segmentation of Gliomas in Pre-Operative and Post-Operative Multimodal Magnetic Resonance Imaging Volumes Based on a Hybrid Generative-Discriminative Framework", In Proceedings of the Multimodal Brain Tumor Image Segmentation Challenge held in conjunction with MICCAI 2016 (MICCAI-BRATS 2016).
    (Athens, Greece, 17-21 Oct 2016)
  5. Spyridon Bakas, Ke Zeng, Aristeidis Sotiras, Saima Rathore, Hamed Akbari, Bilwaj Gaonkar, Martin RozyckiSarthak Pati, Christos Davatzikos. "GLISTRboost: Combining Multimodal MRI Segmentation, Registration, and Biophysical Tumor Growth Modeling with Gradient Boosting Machines for Glioma Segmentation", Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, Springer, LNCS, 9556:144-155, 2016. DOI: 10.1007/978-3-319-30858-6_13
    (Technische Universität München (T.U.M.), Munich, Germany, 5-9 Oct 2015)
    (Publisher's Version)
  6. Spyridon Bakas, Ke Zeng, Aristeidis Sotiras, Saima Rathore, Hamed Akbari, Bilwaj Gaonkar, Martin RozyckiSarthak Pati, Christos Davatzikos. "Segmentation of Gliomas in Multimodal Magnetic Resonance Imaging Volumes Based on a Hybrid Generative-Discriminative Framework", In Proceedings of the Multimodal Brain Tumor Image Segmentation Challenge held in conjunction with MICCAI 2015 (MICCAI-BRATS 2015).
    (Technische Universität München (T.U.M.), Munich, Germany, 5-9 Oct 2015)
  7. Spyridon Bakas, Katerina Chatzimichail, Paul SidhuDimitrios Makris. "Automatic Identification and Localisation of Potential Malignancies in Contrast-Enhanced Ultrasound Liver Scans Using Spatio-Temporal Features", 6th MICCAI Workshop on Abdominal Imaging - Computational and Clinical Applications, Springer, LNCS, 8676:13-22, 2014. DOI: 10.1007/978-3-319-13692-9_2
    (Massachusetts Institute of Technology (M.I.T.), Boston, U.S.A., 14-18 Sep 2014)
    (View)  —  (Publisher's Version)
  8. Spyridon Bakas, Bastien Labbe, Gordon J.A. HunterPaul Sidhu, Katerina Chatzimichail, Dimitrios Makris. "Fast Segmentation of Focal Liver Lesions in Contrast-Enhanced Ultrasound Data", In Proceedings of the 18th Annual Conference on Medical Image Understanding and Analysis (MIUA), 73-78, 2014. DOI: 10.13140/2.1.1769.0400
    (London, U.K., 9-11 Jul 2014)
    (View)  —  (Publisher's Version)
  9. Spyridon Bakas, Bastien Labbe, Gordon J.A. Hunter. "Making the Best Use of Fifty (or more) Shades of Gray: Intelligent Contrast Optimisation for Image Segmentation in False-Colour Video", 10th International Conference on Intelligent Environments - IE'14, IEEE, 218-221, 2014. DOI: 10.1109/IE.2014.41
    (Shanghai, China, 30 Jun-4 Jul 2014)
    (View)  —  (Publisher's Version)
  10. Spyridon BakasPaul SidhuMaria SellarsGordon J.A. HunterDimitrios Makris, Katerina Chatzimichail. "Non-Invasive Offline Characterisation of Contrast-Enhanced Ultrasound Evaluations of Focal Liver Lesions: Dynamic Assessment Using a New Tracking Method", 20th European Congress of Radiology, European Society of Radiology, 2014. DOI: 10.1594/ecr2014/C-1378
    (Vienna, Austria, 6-10 Mar 2014)
    (View)  —  (Publisher's Version)
  11. Spyridon BakasGordon J.A. Hunter, Celia Thiebaud, Dimitrios Makris. "Spot the Best Frame: Towards Intelligent Automated Selection of the Optimal Frame for Initialisation of Focal Liver Lesion Candidates in Contrast Enhanced Ultrasound Video Sequences",9th International Conference on Intelligent Environments - IE'13, IEEE, 196-203, 2013. DOI: 10.1109/IE.2013.20
    (Athens, Greece, 18-19 Jul 2013)
    (View)  —  (Publisher's version)
  12. Spyridon Bakas, Katerina Chatzimichail, Andreas Hoppe, Vasileios Galariotis, Gordon HunterDimitrios Makris. "Focal Liver Lesion Tracking in CEUS for Characterisation based on Dynamic Behaviour", Springer, Advances in Visual Computing, 8th International Symposium on Visual Computing (ISVC), LNCS, 7431:32-41, 2012. DOI: 10.1007/978-3-642-33179-4_4
    (Crete, Greece, 16-18 July 2012)
    (View)  —  (Publisher's version)
  13. Spyridon Bakas, Katerina Chatzimichail, Awen Autret, Andreas Hoppe, Vasileios Galariotis, Dimitrios Makris. "Localisation and characterisation of focal liver lesions using contrast-enhanced ultrasonographic visual cues", In Proceedings of the 15th Annual Conference on Medical Image Understanding and Analysis (MIUA), 2011. DOI: 10.13140/2.1.1474.1280
    (London, U.K., 14 - 15 July 2011)
    (View)  —  (Publisher's version)

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Abstracts

  1. Saima Rathore, Spyridon Bakas, Hamed Akbari, Gaurav Shukla, Martin Rozycki, Christos Davatzikos, “Deriving stable multi-parametric MRI radiomic signatures in the presence of inter-scanner variations: survival prediction of glioblastoma via imaging pattern analysis and machine learning techniques”, In Proc SPIE Medical Imaging, Computer-Aided Diagnosis, Vol.MI103, 2018, DOI 10.1117/12.2293661
  2. Spyridon Bakas, Gaurav Shukla, Hamed Akbari, Aristeidis Sotiras, Guray Erus, Martin Rozycki, Gregory S. Alexander, Joseph Lombardo, Taki Shinohara, Christos Davatzikos, “Accurate and generalizable pre-operative prognostic stratification of glioblastoma patients using integrative quantitative radiomic analysis of conventional MRI”, Neuro-Oncology 19(suppl6):vi151, 2017, DOI: 10.1093/neuonc/nox168.616
    (Presentation at the 22nd Annual Scientific Meeting of the Society for Neuro-Oncology (SNO), San Francisco, California, November 16 - 19, 2017)
  3. Spyridon Bakas, Zev A. Binder, Jennifer J.D. Morrissette, Hamed Akbari, Donald M. O'Rourke, Christos Davatzikos, “Unifying magnetic resonance imaging signature of EGFR pathway activation in glioblastoma consistent with uniformly aggressively infiltration”, Neuro-Oncology 19(suppl6):vi143, 2017, DOI: 10.1093/neuonc/nox168.586
    (Presentation at the 22nd Annual Scientific Meeting of the Society for Neuro-Oncology (SNO), San Francisco, California, November 16 - 19, 2017)
  4. Spyridon Bakas*, Amy H. Thorne*, Zev A. Binder*, Paul E. Wileyto, Jennifer Morrissette, Hamed Akbari, Saima Rathore, A.Scott, Christos Davatzikos, Donald M. O'Rourke, Frank Furnari, “EGFR extracellular domain point mutant A289V: A therapeutically targetable driver of glioblastoma invasion”, Neuro-Oncology 19(suppl6):vi85, 2017. DOI: 10.1093/neuonc/nox168.348
    (Oral presentation at the 22nd Annual Scientific Meeting of the Society for Neuro-Oncology (SNO), San Francisco, California, November 16 - 19, 2017)
  5. Melanie E. Schweitzer, Mihaela A. Stavarache, Nicholas Petersen, Spyridon Bakas, Apostolos J. Tsiouris, Christos Davatzikos, Michael G. Kaplitt, Mark M. Souweidane, “Modulation of Convection Enhanced Delivery (CED) distribution using Focused Ultrasound (FUS)”, Neuro-Oncology 19(suppl6):vi272, 2017, DOI: 10.1093/neuonc/nox168.1118
    (Oral Presentation in the 22nd Annual Scientific Meeting of the Society for Neuro-Oncology (SNO) and the Society for CNS Interstitial Delivery of Therapeutics (SCIDOT) Joint Conference on Therapeutic Delivery to the CNS, 2017)
  6. Sarthak Pati, Spyridon Bakas, Aristeidis Sotiras, Ratheesh Kalarot, Patmaa Sridharan, Mark Bergman, Saima Rathore, Hamed Akbari, Paul Yushkevich, Taki Shinohara, Yong Fan, Despina Kontos, Ragini Verma, Christos Davatzikos, "Cancer Imaging Phenomics Toolkit (CaPTk): A Radio(geno)mics Software Platform Leveraging Quantitative Imaging Analytics for Computational Oncology", 2017
    (Presentation in the Quantitative Imaging Reading Room Showcase, in the 103rd Scientific Assembly and Annual Meeting of the Radiological Society of North America (RSNA), Chicago, Illinois, U.S.A., 26 November – 1 December 2017)
  7. Hamed AkbariSpyridon Bakas, Xiao Da, Donald M. O'RourkeChristos Davatzikos, "Non-invasive Molecular and Prognostic Stratification of de novo Glioblastoma Patients through Multivariate Radiomic Analysis of Baseline Preoperative Multimodal Magnetic Resonance Imaging", 2017
    (Oral Presentation in 10th World Molecular Imaging Congress (WMIC), Philadelphia, Pennsylvania, U.S.A., 13 – 16 September 2017)
  8. Gaurav Shukla, Spyridon Bakas, Saima Rathore, Hamed Akbari, Aristeidis SotirasChristos Davatzikos, "Radiomic Features From Multi-Institutional Glioblastoma MRI Offer Additive Prognostic Value to Clinical and Genomic Markers: Focus on TCGA-GBM Collection", 2017
    (Presentation in the 59st Annual Meeting of the American Society for Radiation Oncology (ASTRO), San Diego, California, U.S.A., 24-27 September 2017)
  9. Jared M.Pisapia, Hamed Akbari, Martin Rozycki, Hannah Goldstein, Spyridon Bakas, Julie S. Moldenhauer, Phillip B. Storm, Deborah M. Zarnow, Richard C.E. Anderson, Gregory G. Heuer, Christos Davatzikos, “Fetal ventriculomegaly: Predicting the need for post-natal cerebrospinal fluid diversion using image analysis and machine learning techniques”. 2017
    (Presentation in the International Symposium on the Fetal Brain, Washington, D.C., August 2017)
  10. Spyridon Bakas, Zev A. Binder, Hamed Akbari, Maria Martinez-Lage, Martin Rozycki, Jennifer J.D. Morrissette, Nadia Dahmane, Donald M. O'Rourke, Christos Davatzikos, "Highly-expressed wild-type EGFR and EGFRvIII mutant glioblastomas have similar MRI signature, consistent with deep peritumoral infiltration", Neuro-Oncology, 18(Suppl.6):VI125-VI126, 2016, DOI: 10.1093/neuonc/now212.523
    (Oral Presentation in the 21st Annual Scientific Meeting of the Society for Neuro-Oncology (SNO), Scottsdale, Arizona, U.S.A., 17-20 November 2016)
  11. Zev A. Binder, Spyridon Bakas, E. Paul Wileyto, Hamed Akbari, Saima Rathore, Martin Rozycki, Jennifer J.D. Morrissette, Maria Martinez-Lage, Nadia Dahmane, Christos DavatzikosDonald M. O'Rourke, "Extracellular EGFR289 activating mutations confer poorer survival and exhibit radiographic signature of enhanced motility in primary glioblastoma", Neuro-Oncology, 18(Suppl.6):VI105-VI106, 2016, DOI: 10.1093/neuonc/now212.441 
    (Presented in the 21st Annual Scientific Meeting of the Society for Neuro-Oncology (SNO), Scottsdale, Arizona, U.S.A., 17-20 November 2016)
  12. Saima Rathore, Hamed Akbari, Martin Rozycki, Spyridon BakasChristos Davatzikos, "Imaging pattern analysis reveals three distinct phenotypic subtypes of GBM with different survival rates", Neuro-Oncology, 18(Suppl.6):VI128, 2016, DOI: 10.1093/neuonc/now212.532 
    (Presented in the 21st Annual Scientific Meeting of the Society for Neuro-Oncology (SNO), Scottsdale, Arizona, U.S.A., 17-20 November 2016)
  13. Jared M. Pisapia, Martin Rozycki, Hamed Akbari, Hannah E. Goldstein, Spyridon Bakas, Julie S. Moldenhauer, Phillip B. Storm, Deborah M. Zarnow, Richard C. E. Anderson, Gregory G. Heuer, Christos Davatzikos, "Fetal Ventriculomegaly: External validity of a fetal MRI-based model to predict the need for post-natal CSF diversion", 2016.
    (Oral Presentation in the 44th Annual Meeting of the International Society for Pediatric Neurosurgery, Kobe, Japan)
  14. Jared M. Pisapia, Hamed AkbariSpyridon Bakas, Martin Rozycki, Julie S. Moldenhauer, Phillip B. Storm, Deborah M. Zarnow, Gregory G. Heuer, Christos Davatzikos, "Fetal Ventriculomegaly: Predicting Need for Post-Natal Shunt using Machine Learning and Fetal MRI", 2015.
    (Oral Presentation in the 44th Annual Meeting of the AANS/CNS Section on Pediatric Neurological Surgery, Seattle, Washington, U.S.A., 8-11 December 2015)
  15. Jared M. Pisapia, Hamed AkbariSpyridon Bakas, Martin Rozycki, Julie S. Moldenhauer, Jayesh P. Thawani, Phillip B. Storm, Deborah M. Zarnow, Christos Davatzikos, Gregory G. Heuer. "Fetal Ventriculomegaly: Ventricle Size Correlates Better with Atrial Diameter than with Fronto-Occipital Horn Ratio", 2015.
    (Presented in the 44th Annual Meeting of the AANS/CNS Section on Pediatric Neurological Surgery, Seattle, Washington, U.S.A., 8-11 December 2015)
  16. Hamed AkbariSpyridon Bakas, Martin Rozycki, Xiao Da, Jared Pisapia, Michel BilelloDonald M. O'RourkeChristos Davatzikos "Non-Invasive Determination of Epidermal Growth Factor Receptor Variant III Expression in Glioblastoma through Analysis of Multi-Parametric Magnetic Resonance Imaging", 2015
    (Oral Presentation in 101st Scientific Assembly and Annual Meeting of the Radiological Society of North America (RSNA), Chicago, Illinois, U.S.A., 29 November – 4 December 2015)
  17. Spyridon Bakas, Hamed Akbari, Jared Pisapia, Martin Rozycki, Donald M. O'Rourke, Christos Davatzikos, "Identification of Imaging Signatures of the Epidermal Growth Factor Receptor Variant III (EGFRvIII) in Glioblastoma", Neuro-Oncology, 17(Suppl.5):V154, 2015, DOI: 10.1093/neuonc/nov225.05
    (Oral Presentation in the 20th Annual Scientific Meeting of the Society for Neuro-Oncology (SNO), San Antonio, Texas, U.S.A., 19-22 November 2015)
  18. Spyridon BakasChristos Davatzikos, "Predictive Modeling in Brain Cancer Using Machine Learning, Imaging and Genomics: Using Informatics to Obtain Rich Characterizations of Aggressive Brain Tumors, in Support of Precision Medicine", Invited talk in MICCAI NIH Workshop on Computational Precision Medicine II, 2015.
    (Presented in the Technische Universität München (T.U.M.), Munich, Germany, 5-9 Oct 2015)
  19. Spyridon BakasBilwaj GaonkarChristos Davatzikos, "Improved Prediction of Post-surgical Survival in Glioblastoma Through Integrative Genomic and Epigenomic Analysis", The Cancer Genome Atlas' 4th Annual Scientific Symposium, 2015. DOI: 10.13140/RG.2.1.1156.1841
    (Presented in the National Institutes of Health (NIH) Campus, Bethesda, MD, U.S.A., 11-12 May 2015)

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Data

  1. Spyridon Bakas, Hamed Akbari, Aristeidis Sotiras, Michel Bilello, Martin Rozycki, Justin Kirby, John Freymann, Keyvan Farahani, Christos Davatzikos. "Segmentation Labels and Radiomic Features for the Pre-operative Scans of the TCGA-GBM collection", The Cancer Imaging Archive, 2017.    DOI: 10.7937/K9/TCIA.2017.KLXWJJ1Q
  2. Spyridon Bakas, Hamed Akbari, Aristeidis Sotiras, Michel Bilello, Martin Rozycki, Justin Kirby, John Freymann, Keyvan Farahani, Christos Davatzikos. "Segmentation Labels and Radiomic Features for the Pre-operative Scans of the TCGA-LGG collection", The Cancer Imaging Archive, 2017.    DOI: 10.7937/K9/TCIA.2017.GJQ7R0EF

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Media

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Theses

  • "Computer-Aided Localisation, Segmentation and Quantification of Focal Liver Lesions in Contrast-Enhanced Ultrasound", Kingston University - Faculty of Science, Engineering & Computing (SEC) - Digital Imaging Research Centre (DIRC) - BioImaging Group (BIG)
    (Ph.D. Thesis - 2014)
  • "Discriminative vs. Generative Methods for Face Detection", University College London (UCL) - Department of Computer Science (CS) - Vision, Imaging & Virtual Environments
    (M.Sc. Thesis - 2007)
  • "Three-Dimensional Reconstruction from Two-Dimensional Representations", Kingston University - Faculty of Technology - School of Computing and Information Systems
    (B.Sc. Dissertation - 2005)

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Software

  • Peritumoral Heterogeneity Index (PHI) Estimator is a lightweight tool, built towards the following goals:
    - Perform quantitative pattern analysis of the spatial heterogeneity of peritumoral perfusion imaging dynamics, retrieved from Dynamic Susceptibility Contrast Magnetic Resonance Imaging (DSC-MRI) data.
    - Evaluate the imaging biomarker of the Epidermal Growth Factor Receptor variant III (EGFRvIII) mutation status, in individual patients diagnosed with glioblastoma.
  • Cancer and Phenomics Toolkit (CapTk) showcases some of the highlight applications from the Center for Biomedical Image Computing and Analytics (CBICA) along with advanced visualization and interactive capabilities to make it a complete radiological tool. It provides the initialization front-end for:
    GLISTRboost (The best performing method during BRATS 2015 challenge)
    - GLioma Image SegmenTation and Registration (GLISTR)
    - Pre-Operative and post-Recurrence brain Tumor Registration (PORTR)
    and entails the functionality of:
    - Evaluating the status of the EGFRvIII mutant in pre-operative scans of patients with brain tumors
    - Producing parametric probability maps of infiltration/recurrence of brain glioblastoma
    - Performing a segmentation of brain tumors using a geodesic segmentation
  • GLISTRboost: Boosted GLioma Image SegmenTation and Registration describes a hybrid generative-discriminative method for segmenting low- and high-grade gliomas in multimodal MRI volumes. Note that this is the winning method of the Multimodal Brain Tumor Image Segmentation (BRATS) Challenge, held in conjunction with the Medical Image Computing and Computer Assisted Intervention (MICCAI) conference in Technische Universitaet Muenchen (TUM) in Munich (Germany) - October 2015
  • GLioma Image SegmenTation and Registration (GLISTR) is a software package designed for jointly segmenting multimodal MRI brain scans of glioma patients and registering these scans to a normal, healthy atlas under an Expectation-Maximisation framework.
  • Brain Tumor Viewer (BTV) is a lightweight viewer, built for fast and simple interaction with MRI image volumes. BTV is primarily designed for visualizing multimodal MRI brain volumes and initializing seed-points for the following software packages:
    - GLioma Image SegmenTation and Registration (GLISTR)
    - Pre-Operative and post-Recurrence brain Tumor Registration (PORTR)
    After initializing these seed-points, a user can generate execution scripts through BTV's graphical user interface for various platforms and custom input parameters.

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