The Division of Computational Pathology, directed by Spyridon Bakas, PhD, addresses clinical requirements by developing, validating and operationalizing cutting-edge computational solutions that drive innovation in diagnostics, patient management, treatment and health care delivery, while promoting excellence in research, education and clinical care.
The division works across IU School of Medicine's tripartite mission areas:
Developing and validating diagnostic, prognostic and predictive computational biomarkers.
Furthering disease knowledge with data-driven approaches.
Understanding underlying factors that drive algorithmic decision.
Bridging the knowledge gap between clinicians and computational scientists.
Mentoring and inspiring the next generation of computational pathology researchers.
Optimization of intuitive interfaces for digital pathology workflow.
Operationalization of digital pathology IT workflow.
Enhanced clinical care through computational innovation.
We envision a health care system where every patient benefits from operationalized reliable computational solutions, which augment the diagnostic capabilities of physicians and optimize patient-centric decision-making.
Sally Atcheson
Associate Director of Academic Research Administration
Keith Koontz
IT Support Leader
Angeliki Papavasileiou
Administrative Coordinator
Wheatley Jordan Leigh
Grant Consultant
Ashlee J Roell
Research Program Manager
Assistant Professor, Department of Biomedical Engineering, Georgia Institute of Technology and Emory University
Research Analyst, Hallym University, Republic of Korea
Director of Research, Department of Biomedical Engineering, Georgia Institute of Technology and Emory University
Former Software Architect
Decentralized approaches to AI make it easier for scientists to share data, protect sensitive data and develop tools that reflect the diversity of patients.
L.Maier-Hein, A.Reinke, P.Godau, M.D.Tizabu, F.Buettner, E.Christodoulou, B.Glocker, F.Isensee, J.Kleesiek, M.Kozubek, M.Reyes, M.A.Riegler, M.Wiesenfarth, A.E.Kavur, C.H.Sudre, M.Baumgartner, M.Eisenmann, D.Heckmann-Nötzel, T.Rädsch, L.Acion, M.Antonelli, T.Arbel, S.Bakas, A.Benis, M.B.Blaschko, M.J.Cardoso, V.Cheplygina, B.Cimini, G.S.Collins, K.Farahani, L.Ferrer, A.Galdran, B.van Ginneken, R.Haase, D.A.Hashimoto, M.M.Hoffman, M.Huisman, P.Jannin, C.E.Kahn, D.Kainmueller, B.Kainz, A.Karargyris, A.Karthikesalingam, F.Kofler, A.Kopp-Schneider, A.Kreshuk, T.Kurc, B.A.Landman, G.Litjens, A.Madani, K.Maier-Hein, A.L.Martel, P.Mattson, E.Meijering, B.Menze, K.G.M.Moons, H.Müller, B.Nichyporuk, F.Nickel, J.Petersen, N.Rajpoot, N.Rieke, J.Saez-Rodriguez, C.I.Sanchez, S.Shetty, M.van Smeden, R.M.Summers, A.A.Taha, A.Tiulpin, S.A.Tsaftaris, B.V.Calster, G.Varoquaux, P.F.Jäger, “Metrics reloaded: Recommendations for image analysis validation”, Nature Methods, [In Press] (arXiv preprint arXiv:2206.01653), 2023
A.Reinke, M.D.Tizabi, M.Baumgartner, M.Eisenmann, D.Heckmann-Nötzel, A.E.Kavur, T.Rädsch, C.H.Sudre, L.Acion, M.Antonelli, T.Arbel, S.Bakas, A.Benis, F.Buettner, M.J.Cardoso, V.Cheplygina, J.Chen, E.Christodoulou, B.A.Cimini, K.Farahani, L.Ferrer, A.Galdran, B.v.Ginneken, B.Glocker, P.Godau, D.A.Hashimoto, M.M.Hoffman, M.Huisman, F.Isensee, P.Jannin, C.E.Kahn, D.Kainmueller, B.Kainz, A.Karargyris, J.Kleesiek, F.Kofler, T.Kooi, A.Kopp-Schneider, M.Kozubek, A.Kreshuk, T.Kurc, B.A.Landman, G.Litjens, A.Madani, K.Maier-Hein, A.L.Martel, E.Meijering, B.Menze, K.G.M.Moons, H.Müller, B.Nichyporuk, F.Nickel, J.Petersen, S.M.Rafelski, N.Rajpoot, M.Reyes, M.A.Riegler, N.Rieke, J.Saez-Rodriguez, C.I.Sánchez, S.Shetty, R.M.Summers, A.A.Taha, A.Tiulpin, S.A.Tsaftaris, B.v.Calster, G.Varoquaux, Z.R.Yaniv, P.F.Jäger, L.Maier-Hein, “Understanding metric-related pitfalls in image analysis validation”, Nature Methods, [In Press] (arXiv preprint arXiv:2302.01790), 2023.
C.G.Filippi, J.M.Stein, Z.Wang, S.Bakas, Y.Liu, P.D.Chang, Y.Lui, C.Hess, D.P.Barboriak, A.E.Flanders, M.Wintermark, G.Zaharchuk, O.Wu, “Ethical Considerations and Fairness in the Use of Artificial Intelligence for Neuroradiology”, AJNR Am. J. Neuroradiol., 44(11):1242-1248, 2023
J.Lost, T.Verma, L.Jekel, M.v.Reppert, N.Tillmanns, S.Merkaj, G.C.Petersen, R.Bahar, A.Gordem, M.A.Haider, H.Subramanian, W.Brim, I.Ikuta, A.Omuro, G.M.Conte, B.V.Marquez-Nostra, A.Avesta, K.Bousabarah, A.Nabavizadeh, A.F.Kazerooni, S.Aneja, S.Bakas, M.Lin, M.Sabel, M.Aboian, “Systematic Literature Review of Machine Learning Algorithms Using Pre-Therapy Radiological Imaging for Glioma Molecular Subtype Prediction”, AJNR Am. J. Neuroradiol., (Online ahead of print), 2023
T.M.Malta, T.S.Sabedot, N.S.Morosini, I.Datta, L.Garofano, W.Vallentgoed, F.S.Varn, K.Aldape, F.D’Angelo, S.Bakas, J.S.Barnholtz-Sloan, H.K.Gan, M.Hasanain, A.-C.Hau, K.C.Johnson, M.Khasraw, E.Kocakavuk, M.C.M.Kouwenhoven, S.Migliozzi, S.P.Niclou, J.M.Niers, D.R.Ormond, S.H.Paek, G.Reifenberger, P.A.S.Smitt, M.Smits, L.F.Stead, M.J.van den Bent, E.G.V.Meir, A.Walenkamp, T.Weiss, M.Weller, B.A.Westerman, B.Ylstra, P.Wesseling, A.Lasorella, P.J.French, L.M.Poisson, R.G.W.Verhaak, A.Iavarone, H.Noushmehr, “The epigenetic evolution of gliomas is determined by their IDH1 mutation status and treatment regimen”, Cancer Research [Online ahead of print], 2023. doi: 10.1158/0008-5472.CAN-23-2093.
P.Whybra, A.Zwanenburg, V.Andrearczyk, R.Schaer, A.P.Apte, A.Ayotte, B.Baheti, S.Bakas, A.Bettinelli, R.Boellaard, L.Boldrini, I.Buvat, G.J.R.Cook, F.Dietsche, N.Dinapoli, H.S.Gabryś, V.Goh, M.Guckenberger, M.Hatt, M.Hosseinzadeh, A.Iyer, J.Lenkowicz, M.A.L.Loutfi, S.Löck, F.Marturano, O.Morin, C.Nioche, F.Orlhac, S.Pati, A.Rahmim, S.M.Rezaeijo, C.G.Rookyard, M.R.Salmanpour, A.Schindele, I.Shiri, E.Spezi, S.Tanadini-Lang, F.Tixier, T.Upadhaya, V.Valentini, J.J.M.v.Griethuysen, F.Yousefirizi, H.Zaidi, H.Müller, M.Vallières, A.Depeursinge, “The Image Biomarker Standardization Initiative: Standardized convolutional filters for quantitative radiomics”, arXiv preprint arXiv:2006.05470, Radiology (In Press), 2023
S.Innani, P.Dutande, U.Baid, V.Pokuri, S.Bakas, S.Talbar, B.Baheti, S.C.Guntuku, “Generative adversarial networks based skin lesion segmentation”, Nature Scientific Reports, 13:13467, 2023.
S.M.Rezaeijo, N.Chegeni, F.B.Naeini, D.Makris, S.Bakas, “Within-Modality Synthesis and Novel Radiomic Evaluation of Brain MRI Scans”, Cancers, 15(14), 2023.
M.D.Lee, S.H.Patel, S.Mohan, H.Akbari, S.Bakas, M.P.Nasrallah, E.Calabrese, J.Rudie, J.Villanueva-Meyer, P.LaMontagne, D.S.Marcus, R.R.Colen, C.Balana, Y.S.Choi, C.Badve, J.S.Barnholtz-Sloan, A.E.Sloan, T.C.Booth, J.D.Palmer, A.P.Dicker, A.E.Flanders, W.Shi, B.Griffith, L.M.Poisson, A.Chakravarti, A.Mahajan, S.Chang, D.Orringer, C.Davatzikos, R.Jain, “Association of partial T2-FLAIR mismatch sign and isocitrate dehydrogenase mutation in WHO grade 4 gliomas: results from the ReSPOND consortium”, Neuroradiology, 65:1343–1352, 2023.\
A. Karargyris, R. Umeton, M. Sheller, A. Aristizabal, J. George, A. Wuest, S. Pati, H. Kassem, M. Zenk, U. Baid, P. N. Moorthy, A. Cowdhury, J. Guo, S. Nalawade, J. Rsenthal, D. Kanter, M. Xenochristou, D. Beutel, V. Chung, T. Bergquist , J. Eddy, A. Abid, L. Tunstall, O. Sanseviero, D. Dimitriadis, Y. Qian, X. Xu, Y. Lio, R. S.M. Goh, S. Bala, V. Bittorf, S. R. Puchala, B. Riciuti, S. Samineni, E. Sengupta, A. Chaudhari, C. Coleman, B. Desinghu, G. Diamos, D. Dutta, D. Feddema, G. Fursin, X. Huang, S. Kashyap, N. Lane, I. Mallick, F. Consortium, B. Consortium, A. Consortium, C. Consortium,, P. Mascagni, V. Mehta, C. F. Moraes, V. Natarajan, N. Nikolov, N. Padoy, G. Pekhimenko, V. J. Reddi , G. A. Reina, P. Ribalta, A. Sing, J. J. Thiagarajana, J. Albrecht, T. Wolf, G. Miller, H. Fu, P. Shah, D. Xu, P. Yadav, D. Talby, M. M. Awad, J. P. Howard, M. Rosenthal, L. Marchionni, M. Loda, J. M. Johnson, P. Mattson*, S. Bakas*, “Federated Benchmarking of Medical Artificial Intelligence with MedPerf”, Nature Machine Intelligence, 5:799–810, 2023.
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, “GaNDLF: The Generally Nuanced Deep Learning Framework for Scalable End-to-End Clinical Workflows”, Nature Communications Engineering, 2(1), 2023.
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, “Are we using appropriate segmentation metrics? Identifying correlates of human expert perception for CNN training beyond rolling the DICE coefficient”, Journal of Machine Learning for Biomedical Imaging (MELBA), 2, 2023:002, 2023.
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, “CheckList for EvaluAtion of Radiomics research (CLEAR): a step-by-step reporting guideline for authors and reviewers endorsed by ESR and EuSoMII”, Insights Into Imaging, 14(75), 2023.
Z.R.Samani, D.Parker, H.Akbari, R.L.Wolf, S.Brem, S.Bakas, R.Verma, “Artificial intelligence-based locoregional markers of brain peritumoral microenvironment”, Nature Scientific Reports, 13(1):963, 2023.
R.Dorent, A.Kujawa, M.Ivory, S.Bakas, N.Rieke, S.Joutard, B.Glocker, J.Cardoso, M.Modat, K.Batmanghelich, A.Belkov, M.B.Calisto, J.W.Choi, B.M.Dawant, H.Dong, S.Escalera, Y.Fan, L.Hansen, M.P.Heinrich, S.Joshi, V.Kashtanova, H.G.Kim, S.Kondo, C.N.Kruse, S.K.Lai-Yuen, H.Li, H.Liu, B.Ly, I.Oguz, H.Shin, B.Shirokikh, Z.Su, G.Wang, J.Wu, Y.Xu, K.Yao, L.Zhang, S.Ourselin, J.Shapey, T.Vercauteren, ”CrossMoDA 2021 challenge: Benchmark of Cross-Modality Domain Adaptation techniques for Vestibular Schwnannoma and Cochlea Segmentation”, Medical Image Analysis, 83, 102628, 2023.
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, “Why is the winner the best?”, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), [In Press], 2023 [arXiv preprint arXiv:2303.17719]
B.Baheti, S.Innani, G.Mehdiratta, M.P.Nasrallah, S.Bakas, “Interpretable whole slide image prognostic stratification of glioblastoma patients furthering current disease understanding”, Neuro-Oncology, 25(Suppl.2):ii103-ii104, 2023.
B.Baheti, S.Innani, M.P.Nasrallah, S.Bakas, “A unsupervised clustering of morphology patterns on whole slide images guide prognostic stratification of glioblastoma patients”, Neuro-Oncology, 25(Suppl.2):ii15, 2023. [Oral Presentation at EANO 2023]
S.Pati, U.Baid, B.Edwards, M.Sheller, J.Martin, A.Karargyris, S.Bakas, “The Comprehensive Open Federated Ecosystem (COFE): Enabling impactful healthcare studies”, Pendergrass Symposium (University of Pennsylvania, Philadelphia, PA USA), June 2023. (Plenary session: higher distinction than Summa Cum Laude)
B.Baheti, S.Innani, G.Mehdiratta, M.P.Nasrallah,S.Bakas, “Interpretable whole slide image prognostic stratification of glioblastoma patients furthering current clinical knowledge”, 19th European Congress on Digital Pathology (ECDP), 2023.
B.Baheti, S.Innani, M.P.Nasrallah, S.Bakas, “Unsupervised clustering of morphology patterns on whole slide images guide prognostic stratification of glioblastoma patients”, 19th European Congress on Digital Pathology (ECDP), 2023.
S.Pati, S.Bakas, “Federated Learning and Reproducibility in Healthcare”, Proceedings of the Dagstuhl Seminar Series, 2023
S.Innani, B.Baheti, M.P.Nasrallah, S.Bakas, "Interpretable IDH classification from H&E-stained histology slides", Neuro-Oncology, Volume 25, Issue Supplement_5, November 2023, Page v177, https://doi.org/10.1093/neuonc/noad179.0669
B.Baheti, S.Rai, S.Innani, G.Mehdiratta, S.C.Guntuku, M.P.Nasrallah, S.Bakas, "Detecting Histologic & Clinical Glioblastoma Patterns Of Prognostic Relevance", Neuro-Oncology, Volume 25, Issue Supplement_5, November 2023, Page v126, https://doi.org/10.1093/neuonc/noad179.0478
A.Gastounioti, O.H.Maghsoudi, S.Rathore, E.F.Conant, D.Kontos, S.Bakas. Chapter: Computational Applications in Brain and Breast Cancer, “Book: State of the Art in Neural Networks”, Elsevier, 2023.
D.Ramakrishnan, L.Jekel, S.Chadha, A.Janas, H.Moy, N.Maleki, M.Sala, M.Kaur, G.C.Petersen, S.Merkaj, M.vonReppert, U.Baid, S.Bakas, C.Kirsch, M.Davis, K.Bousabarah, W.Holler, M.Lin, M.Westerhoff, S.Aneja, F.Memon, M.S.Aboian, “A Large Open Access Dataset of Brain Metastasis 3D Segmentations on MRI with Clinical and Imaging Feature Information (Version 1) [dataset]”. The Cancer Imaging Archive, 2023. DOI: https://doi.org/10.7937/6be1-r748
M.E.Celebi, M.S.Salekin, H.Kim, S.Albarqouni, C.Barata, A.Halpern, P.Tschandl, M.Combalia, Y.Liu, G.Zamzmi, J.Levy, H.Rangwala, A.Reinke , D.Wynn, B.Landman, W.-K.Jeong, Y.Shen, Z.Deng, S.Bakas, X.Li, C.Qin, N.Rieke, H.Roth, D.Xu, “Medical Image Computing and Computer Assisted Intervention – MICCAI 2023 Workshops”, ISIC 2023, Care-AI 2023, MedAGI 2023, DeCaF 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8–12, 2023, Proceedings, Lecture Notes in Computer Science book series (LNCS 14393)
