Spyridon Bakas, PhD
Assistant Professor of Pathology and Laboratory MedicinePerelman School of Medicine at the University of Pennsylvania
Contact InformationUniversity of Pennsylvania
Richards Medical Research Laboratories
3700 Hamilton Walk
Floor 7
Philadelphia, PA, 19104
Office: 267-752-5209
Email: sbakas@upenn.edu
Specialty Division
Immunobiology and Experimental Pathology
Research Expertise
Biomedical Image Analysis
Machine Learning
Cancer Imaging
Radiogenomics
Computational Pathology
Glioblastoma
Pattern Analysis
Itmat Expertise
Computational Pathology;
Radiogenomics;
Machine learning;
Pattern analysis;
Image segmentation
Education
BSc (Hons) (Computer Science), Kingston University London, 2006
MSc (Vision, Imaging & Virtual Environments), University College London, 2007
PhD (Medical Image Computing & Analysis), Kingston University London, 2014
Specialty Certification
Postgraduate Training
Postdoctoral Research Fellow, University of Pennsylvania, 2014-2019
Awards and Honors
Second Prize Award for Best Poster Presentation:
British Machine Vision Association / Engineering and Physical Sciences Research Council Summer School on Computer Vision, 2009
Fully Funded Ph.D. Studentship: Kingston University, Faculty of Science, Engineering and Computing, 2011
First Prize Award for Best Poster Presentation: Kingston University PhD Poster Competition, 2013
First Prize Award for the Best Performing Segmentation Method: International Multimodal Brain Tumor Segmentation (BRATS) Challenge 2015, in conjunction with MICCAI 2015, 2015
Best Clinical Research Presentation: Pan-Philadelphia Neurosurgery Conference, 2015
Featured paper in Newsletter of (NIH/NCI): National Institutes of Health/National Cancer Institute’s "Division of Cancer Treatment and Diagnosis", 2017
Top-ranked abstract and featured at the Highlight Plenary Lecture: World Molecular Imaging Conference, 2017
Featured paper in journal’s frontpage: Nature Scientific Data journal, 2017
Best Abstract Award (First Prize), Annual Radio-Biology and Imaging (RBI) Program Retreat 2017, University of Pennsylvania, 2017
Magna Cum Laude for Scientific Abstract at the 44th Pendergrass Day Symposium of the UPenn: Prognostic Stratification of GBM Patients via Computational Analysis of Preoperative Structural MRI, 2018
Top-ranked & featured as 1/5 Highlights (23rd Annual SNO Meeting): “Non-invasive in vivo signature of IDH1 mutational status in high grade glioma, from clinically-acquired multi-parametric magnetic resonance imaging, using multivariate machine learning”, 2018
Highlighted Conference Session at the IEEE International Symposium on Biomedical Imaging (ISBI) 2018: Half-Day Tutorial on CaPTk featured in the Best-of-ISBI events by Computer Vision News, 2018
First Prize Award for Best Poster Presentation on FeTS Annual Scientific Meeting of the Informatics Technology for Cancer Research (ITCR), 2020
Magna Cum Laude on Scientific Abstract 47th Pendergrass Day Symposium, University of Pennsylvania, 2021
Plenary Talk (competitive award) on Scientific Abstract 47th Pendergrass Day Symposium, University of Pennsylvania, 2021
First Prize Award for Best Oral PresentationInternational Medical Imaging with Deep Learning (MIDL) 2021 conference, 2021
Plenary Talk (competitive award) on Scientific Abstract 48th Pendergrass Day Symposium, University of Pennsylvania Radiogenomic Mapping of Key Driver Genes in GBM in Presence or Absence of Co-occuring Mutations, 2022
2 Summa Cum Laude Designations on Scientific Abstracts, 48th Pendergrass Day Symposium, University of Pennsylvania, May 2022, 2022
First Prize Award for Best Project Presentation on the NIH Annual Scientific Meeting of the Informatics Technology for Cancer Research program: “The Federated Tumor Segmentation (FeTS) platform”, 2022
Annual Lucien Levy Best Research Article Award NomineeAJNR Am. J. Neuroradiol
Quantifying T2-FLAIR Mismatch Using Geographically Weighted Regression & Predicting Molecular Status in Lower-Grade Glioma, 2022
Memberships and Professional Organizations
Member - British Machine Vision Association (BMVA), 2012 - 2015
Member - European Association for Cancer Research, 2013 - Present
Member - British Association for Cancer Research, 2013 - Present
Member, Medical Image Computing & Computer-Assisted Interventions (MICCAI), 2014 - Present
Member - Society for Neuro-Oncology (SNO), 2015 - Present
Member - Institute of Electrical and Electronics Engineers (IEEE), 2017 - 2018
Member - IEEE Engineering in Medicine and Biology Society (IEEE-EMBS), 2017 - 2018
Web Links
Selected Publications
"State of the Art in Neural Networks" (Computational Applications in Brain and Breast Cancer)
A.Gastounioti, O.H.Maghsoudi, S.Rathore, E.F.Conant, D.Kontos, S.Bakas, Elsevier, 2023
“Are we using appropriate segmentation metrics? Identifying correlates of human expert perception for CNN training beyond rolling the DICE coefficient”
F.Kofler, I.Ezhov, F.Isensee, F.Balsiger, C.Berger, M.Koerner, B.Demiray, J.Rackerseder, J.Paetzold, H.Li, S.Shit, R.McKinley, M.Piraud, S.Bakas, C.Zimmer, N.Navab, J.Kirschke, B.Wiestler, B.H.Menze,, Journal of Machine Learning for Biomedical Imaging (MELBA), 2023
“Why is the winner the best?”
M.Eisenmann, A.Reinke, V.Weru, M.D.Tizabi, F.Isensee, T.J.Adler, S.Ali, V.Andrearczyk, M.Aubreville, U.Baid, S.Bakas, N.Balu, S.Bano, J.Bernal, S.Bodenstedt, A.Casella, V.Cheplygina, M.Daum, M.de Bruijne , A.Depeursinge, R.Dorent, J.Egger, D.G.Ellis, S.Engelhardt, M.Ganz, N.Ghatwary, G.Girard, P.Godau, A.Gupta, L.Hansen, K.Harada, M.Heinrich, N.Heller, A.Hering, A.Huaulmé, P.Jannin, A.E.Kavur, O.Kodym, M.Kozubek, J.Li, H.Li, J.Ma, C.Martín-Isla, B.Menze, A.Noble, V.Oreiller, N.Padoy, S.Pati, K.Payette, T.Rädsch, J.Rafael-Patiño, V.Singh Bawa, S.Speidel, C.H.Sudre, K.van Wijnen, M.Wagner, D.Wei, A.Yamlahi, M.Yap, C.Yuan, M.Zenk, A.Zia, D.Zimmerer, D.Aydogan, B.Bhattarai, L.Bloch, R.Brüngel, J.Cho, C.Choi, Q.Dou, I.Ezhov, C.M.Friedrich, C.Fuller, R.R.Gaire, A.Galdran, Á.García Faura, M.Grammatikopoulou, S.Hong, M.Jahanifar, I.Jang, A.Kadkhodamohammadi, I.Kang, F.Kofler, S.Kondo, H.Kuijf, M.Li, M.Luu, T.Martinčič, P.Morais, M.A.Naser, B.Oliveira, D.Owen, S.Pang, J.Park, S.Park, S.Płotka, E.Puybareau, N.Rajpoot, K.Ryu, N.Saeed, A.Shephard, P.Shi, D.Štepec, R.Subedi, G.Tochon, H.R.Torres, H.Urien, J.L.Vilaça, K.A.Wahid, H.Wang, J.Wang, L.Wang, X.Wang, B.Wiestler, M.Wodzinski, F.Xia, J.Xie, Z.Xiong, S.Yang, Y.Yang, Z.Zhao, K.Maier-Hein, P.F.Jäger, A.Kopp-Schneider, L.Maier-Hein, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023
“Artificial intelligence-based locoregional markers of brain peritumoral microenvironment”
Z.R.Samani, D.Parker, H.Akbari, R.L.Wolf, S.Brem, S.Bakas, R.Verma, Nature Scientific Reports, 2023
“CheckList for EvaluAtion of Radiomics research (CLEAR): a step-by-step reporting guideline for authors and reviewers endorsed by ESR and EuSoMII”
B.Kocak*, B.Baessler*, S.Bakas*, R.Cuocolo, A.Fedorov, L.Maier-Hein, N.Mercaldo, H.Muller, F.Orlhac, D.P.Santos, A.Stanzione, L.Ugga, A.Zwanenburg, Insights Into Imaging, 2023
“Interpretable whole slide image prognostic stratification of glioblastoma patients furthering current clinical knowledge”
B.Baheti, S.Innani, G.Mehdiratta, M.P.Nasrallah, S.Bakas, 19th European Congress on Digital Pathology (ECDP), 2023
“Federated Learning and Reproducibility in Healthcare”
S.Pati, S.Bakas, Proceedings of the Dagstuhl Seminar Series,, 2023
“Unsupervised clustering of morphology patterns on whole slide images guide prognostic stratification of glioblastoma patients”
B.Baheti, S.Innani, M.P.Nasrallah, S.Bakas, 19th European Congress on Digital Pathology (ECDP), 2023
“GaNDLF: The Generally Nuanced Deep Learning Framework for Scalable End-to-End Clinical Workflows”
S.Pati, S.P.Thakur, I.E.Hamamci, U.Baid, B.Baheti, M.Bhalerao, O.Guley, S.Mouchtaris, D.Lang, S.Thermos, K.Gotkowski, C.Gonzalez, C.Grenko, A.Getka, B.Edwards, M.Sheller, J.Wu, D.Karkada, R.Panchumarthy, V.Ahluwalia, C.Zou, V.Bashyam, Y.Li, B.Haghighi, R.Chitalia, S.Abousamra, T.M.Kurc, A.Gastounioti, S.Er, M.Bergman, J.H.Saltz, Y.Fan, P.Shah, A.Mukhopadhyay, S.A.Tsaftaris, B.Menze, C.Davatzikos, D.Kontos, A.Karargyris, R.Umeton, P.Mattson, S.Bakas, Nature Communications Engineering, 2023
“Classification of Infection and Ischemia in Diabetic Foot Ulcers Using VGG Architectures”
O.Güley, S.Pati, S.Bakas, Springer – LNCS, 2022
