Computational Pathology

• 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.

Journal Manuscripts

1. H.Akbari, S.Bakas, C.Sako, A.Fathi Kazerooni, J.Villanueva-Meyer, J.A.Garcia, E.Mamourian, F.Liu, Q.Cao, R.T.Shinohara, U.Baid, A.Getka, S.Pati, A.Singh, E.Calabrese, S.Chang, J.Rudie, A.Sotiras, P.LaMontagne, D.S.Marcus, M.Milchenko, A.Nazeri, C.Balana, J.Capellades, J.Puig, C.Badve, J.S.Barnholtz-Sloan, A.E.Sloan, V.Vadmal, K.Waite, M.Ak, R.R.Colen, Y.W.Park, S.S.Ahn, J.H.Chang, Y.S.Choi, S.K.Lee, G.S.Alexander, A.S.Ali, A.P.Dicker, A.E.Flanders, S.Liem, J.Lombardo, W.Shi, G.Shukla, B.Griffith, L.M.Poisson, L.R.Rogers, A.Kotrotsou, T.C.Booth, R.Jain, M.Lee, A.Mahajan, A.Chakravarti, J.D.Palmer, D.DiCostanzo, H.Fathallah-Shaykh, S.Cepeda, O.S.Santonocito, A.L.Di Stefano, B.Wiestler, E.R.Melhem, G.F.Woodworth, P.Tiwari, P.Valdes, Y.Matsumoto, Y.Otani, R.Imoto, M.Aboian, S.Koizumi, K.Kurozumi, T.Kawakatsu, K.Alexander, L.Satgunaseelan, A.M.Rulseh, S.J.Bagley, M.Bilello, Z.A.Binder, S.Brem, A.S.Desai, R.A.Lustig, E.Maloney, T.Prior, N.Amankulor, M.P.Nasrallah, D.M.O’Rourke, S.Mohan, C.Davatzikos, ReSPOND consortium, "Machine learning-based prognostic subgrouping of glioblastoma: A multicenter study", Neuro-Oncology, noae260, 2024
2. V.S.Ahluwalia, N.Doiphode, W.C.Mankowski, E.A.Cohen, S.Pati, L.Pantalone, S.Bakas, A.Brooks, C.M.Vachon, E.F.Conant, A.Gastounioti, D.Kontos, "Volumetric Breast Density Estimation From Three-Dimensional Reconstructed Digital Breast Tomosynthesis Images Using Deep Learning", JCO Clinical Cancer Informatics, 8 (2024): e2400103, 2024
3. S.Bakas, P.Vollmuth, N.Galldiks, T.C.Booth, H.J.W.L.Aerts, W.L.Bi, B.Wiestler, P.Tiwari, S.Pati, U.Baid, E.Calabrese, P.Lohmann, M.Nowosielski, R.Jain, R.Colen, M.Ismail, G.Rasool, J.M.Lupo, H.Akbari, J.C.Tonn, D.Macdonald, M.Vogelbaum, S.M.Chang, C.Davatzikos, J.E.Villanueva-Meyer, R.Y.Huang, "Artificial Intelligence for Response Assessment in Neuro Oncology (AI-RANO), part 2: recommendations for standardisation, validation, and good clinical practice", The Lancet Oncology, 25(11), pp.e589-e601, 2024
4. J.E.Villanueva-Meyer, S.Bakas, P.Tiwari, J.M.Lupo, E.Calabrese, C.Davatzikos, W.L.Bi, M.Ismail, H.Akbari, P.Lohmann, T.C.Booth, B.Wiestler, H.J.W.L.Aerts, G.Rasool, J.C.Tonn, M.Nowosielski, R.Jain, R.R.Colen, S.Pati, U.Baid, P.Vollmuth, D.Macdonald, M.A.Vogelbaum, S.M.Chang, R.Y.Huang, N.Galldiks, "Artificial Intelligence for Response Assessment in Neuro Oncology (AI-RANO), part 1: review of current advancements", The Lancet Oncology, 25(11), pp.e581-e588, 2024
5. A.Afiaz, A.A.Ivanov, J.Chamberlin, D.Hanauer, C.L.Savonen, M.J.Goldman, M.Morgan, M.Reich, A.Getka, A.Holmes, S.Pati, D.Knight, P.C.Boutros, S.Bakas, J.G.Caporaso, G.Del Fiol, H.Hochheiser, B.Haas, P.D.Schloss, J.A.Eddy, J.Albrecht, A.Fedorov, L.Waldron, A.M.Hoffman, R.L.Bradshaw, J.T.Leek, C.Wright, "Best practices to evaluate the impact of biomedical research software—metric collection beyond citations", Bioinformatics, 40(8), btae469, 2024
6. S.Pati, S.Kumar, A.Varma, B.Edwards, C.Lu, L.Qu, J.J.Wang, A.Lakshminarayanan, S.Wang, M.J.Sheller, K.Chang, P.Singh, D.L.Rubin, J.Kalpathy-Cramer, S.Bakas, "Privacy Preservation for Federated Learning in Healthcare", Cell Patterns, Online, 2024
7. 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.van Griethuysen, F.Yousefirizi, H.Zaidi, H.Müller, M.Vallières, A.Depeursinge, "The image biomarker standardization initiative: Standardized convolutional filters for reproducible radiomics and enhanced clinical insights", Radiology, 310(2),e231319, 2024
8. B.Baheti, S.Innani, M.Nasrallah, S.Bakas, "Prognostic Stratification of Glioblastoma Patients by Unsupervised Clustering of Morphology Patterns on Whole Slide Images Furthering Our Disease Understanding", Frontiers in Neuroscience, 18, 1304191, 2024
9. D.Ramakrishnan, L.Jekel, S.Chadha, A.Janas, H.Moy, N.Maleki, M.Sala, M.Kaur, G.CassinelliPetersen, 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 information", Nature Scientific Data, 11(1), 254, 2024
10. B.Kocak, T.A.D’Antonoli, N.Mercaldo, A.Alberich Bayarri, B.Baessler, I.Ambrosini, A.E.Andreychenko, S.Bakas, R.G.H.Beets Tan, K.Bressem, I.Buvat, R.Cannella, L.A.Cappellini, A.U.Cavallo, L.L.Chepelev, L.C.H.Chu, A.Demircioglu, N.M.deSouza, M.Dietzel, S.C.Fanni, A.Fedorov, L.S.Fournier, V.Giannini, R.Girometti, K.B.W.G.Lipman, G.Kalarakis, B.S.Kelly, M.E.Klontzas, D. M.Koh, E.Kotter, H.Y.Lee, M.Maas, L.Marti Bonmati, H.Müller, N.Obuchowski, F.Orlhac, N.Papanikolaou, E.Petrash, E.Pfaehler, D.P.dosSantos, A.Ponsiglione, S.Sabater, F.Sardanelli, P.Seeböck, N.M.Sijtsema, A.Stanzione, A.Traverso, L.Ugga, M.Vallières, L.V.vanDijk, J.J.M.vanGriethuysen, R.W.vanHamersvelt, P.vanOoijen, F.Vernuccio, A.Wang, S.Williams, J.Witowski, Z.Zhang, A.Zwanenburg, R.Cuocolo, "METhodological RadiomICs Score (METRICS): A quality scoring tool for radiomics research endorsed by EuSoMII", Insights Into Imaging, 15(1):8, 2024
11. J.Guo, A.F.Kazerooni, E.Toorens, H.Akbari, F.Yu, C.Sako, E.Mamourian, R.T.Shinohara, C.Koumenis, S.J.Bagley, J.J.D.Morrissette, Z.A.Binder, S.Brem, S.Mohan, R.A.Lustig, D.M.O’Rourke, T.Ganguly, S.Bakas, M.P.Nasrallah, C.Davatzikos,, "Integrating imaging and genomic data for the discovery of distinct glioblastoma subtypes: a joint learning approach", Nature Scientific Reports, 14(1):4922, 2024
12. 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, 21:182-194, 2024
13. 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, 21(2):195-212, 2024
14. D.LaBella, O.Khanna, S.McBurney-Lin, R.Mclean, P.Nedelec, A.S.Rashid, N.H.Tahon, T.Altes, U.Baid, R.Bhalerao, Y.Dhemesh, F.Hilal, A.Janas, A.Fathi Kazerooni, C.Kent, J.Kirkpatrick, F.Kofler, K.Leu, N.Maleki, B.Menze, M.Pajot, Z.J.Reitman, J.D.Rudie, R.Saluja, Y.Velichko, C.Wang, P.I.Warman, N.Sollmann, D.Diffley, K.K.Nandolia, D.I.Warren, A.Hussain, J.P.Fehringer, Y.Bronstein, L.Deptula, E.G.Stein, M.Taherzadeh, E.P.de Oliveira, A.Haughey, M.Kontzialis, L.Saba, B.Turner, M.M.T.Brüßeler, S.Ansari, A.Gkampenis, D.M.Weiss, A.Mansour, I.H.Shawali, N.Yordanov, J.M.Stein, R.Hourani, M.Y.Moshebah, A.M.Abouelatta, T.Rizvi, K.Willms, D.C.Martin, A.Okar, G.D’Anna, A.Taha, Y.Sharifi, S.Faghani, D.Kite, M.Pinho, M.A.Haider, M.Alonso-Basanta, J.Villanueva-Meyer, A.M.Rauschecker, A.Nada, M.Aboian, A.Flanders, S.Bakas*, E.Calabrese*,, "A Multi-Institutional Meningioma MRI Dataset for Automated Multi-Sequence Image Segmentation", Nature Scientific Data, 11(1):496, 2024
15. M.G.Linguraru, S.Bakas, M.Aboian, P.Chang, A.Flanders, J.Kalpathy-Cramer, F.C.Kitamura, M.Lungren, J.Mongan, L.Prevedello, R.M.Summers, C.C.Wu, M.Adewole, C.E.Kahn,, "Clinical, Cultural, Computational, and Regulatory Considerations to Deploy AI in Radiology: Perspectives of RSNA and MICCAI Experts”", Radiology: Artificial Intelligence, 6(4), 2024
16. G.Yang, B.Edwards, S.Bakas, Q.Dou, D.Xu, X.Li, W.Wang,, "Federated learning as a catalyst for digital healthcare innovations", Cell Patterns, 5(7):101026, 2024S.Gongala, J.Garcia, N.Korakavi, N.Patil, H.Akbari, C.Tippareddy, A.Sloan, J.Barnholtz-Sloan, S.Bakas, A.Fathi Kazerooni, C.Sako, U.Baid, S.Brem, R.A Lustig, J.Capellades, M.Nasrallah, D.M O'Rourke, P.LaMontagne, D.S Marcus, C.Balana, J.Puig, K.Waite, R.Colen, Y.Seong Choi, S.Lee, A.P Dicker, A.E Flanders, W.Shi, B.Griffith, L.M Poisson, L.R Rogers, T.C Booth, R.Jain, A.Chakravarti, J.Palmer, S.Mohan, P.Tiwari, M.Aboian, S.Soo Ahn, C.Davatzikos, C.Badve,, "Sex-specific differences in glioblastoma in the ReSPOND consortium", American Journal of NeuroRadiology, 45(9):1299-1307, 2024
17. F.Gomez, A.M.Danos, G.Del Fiol, A.Madabhushi, P.Tiwari, J.F.McMichael, S.Bakas, J.Bian, C.Davatzikos, E.J.Fertig, J.Kalpathy-Cramer, J.Kenney, G.Savova, M.Yetisgen, E.M.Van Allen, J.L.Warner, F.Prior, M.Griffith, O.L.Griffith,, "A new era of data-driven cancer research and care: opportunities and challenges", Cancer Discovery, 14(10):1774-1778, 2024
18. J.L.Agraz, C.Agraz, A.A.Chen, C.Rice, R.S.Pozos, S.Aelterman, A.Tan, A.N.Viaene, M.P.Nasrallah, P.Sharma, C.M.Grenko, T.Kurc, J.Saltz, M.D.Feldman, H.Akbari, R.T.Shinohara, S.Bakas, P.Wilson,, "Optimized Whole-Slide-Image H&E Stain Normalization: A Step Towards Big Data Integration in Digital Pathology", IEEE Open Journal of Engineering in Medicine and Biology, 6:35-40, 2024
19. J.Lost, N.Ashraf, L.Jekel, M.v.Reppert, N.Tillmanns, K.Willms, S.Merkaj, G.C.Petersen, A.Avesta, D.Ramakrishnan, A.Omuro, A.Nabavizadeh, S.Bakas, M.Lin, S.Aneja, M.Sabel, M.Aboian,, "Enhancing Clinical Decision-Making: An Externally Validated Machine Learning Model for Predicting IDH Mutation in Gliomas using Radiomics from Pre-Surgical MRI", NeuroOncology Advances, 6(1), 2024
20. 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, 84(5):741-756, 2024, 2024

Peer Reviewed Full-length Conference Articles

1. I.E.Hamamci, S.Er, A.Sekuboyina, E.Simsar, A.Tezcan, A.G.Simsek, S.N.Esirgun, F.Almas, I.Dogan, M.F.Dasdelen, C.Prabhakar, H.Reynaud, S.Pati, C.Bluethgen, M.K.Ozdemir, B.Menze, "Generatect: Text-conditional generation of 3d chest ct volumes", ECCV, pp. 126-143, 2024
2. S.Innani, B.Baheti, M.P.Nasrallah, S.Bakas, "Weakly Supervised IDH-status glioma classification from H&E-stained whole slide images", ISBI 2024, Athens, Greece, Online, 2024
3. S.Innani, M.P.Nasrallah,W.R.Bell, B.Baheti, S.Bakas, "Multi-scale Whole Slide Image Assessment Improves Deep Learning based WHO 2021 Glioma Classification", MICCAI COMPAYL Workshop 2024, Marrakesh, Morocco, Online, 2024
4. N.Doiphode, V.S.Ahluwalia, W.C.Mankowski, E.A.Cohen, S.Pati, L.Pantalone, S.Bakas, A.Brooks, C.M.Vachon, E.F.Conant, A.Gastounioti, D.Kontos,, "Advancing volumetric breast density segmentation: a deep learning approach with digital breast tomosynthesis", In Proc. 17th Int Workshop on Breast Imaging (IWBI), 13174:131740O, 2024
5. S.Adap, U.Baid, S.Bakas, "Classifying Histopathologic Glioblastoma Sub-regions with EfficientNet", MICCAI Consolidated Brain Analytics Satellite Events Proceedings,, [In Press], , 2024
6. P.Liang, H.Zheng, H.Li, Y.Gong, S.Bakas, Y.Fan,, "Enhancing Whole Slide Image Classification with Discriminative and Contrastive Learning", International Conference on Medical Image Computing and Computer-Assisted Intervention, Springer LNCS, 15004:102-112, 2024
7. D.Waldmannstetter, B.Wiestler, J.Schwarting, I.Ezhov, M.Metz, S.Bakas, B.Baheti, S.Chakrabarty, D.Rueckert, J.S.Kirschke, R.A.Heckemann, M.Piraud, B.H.Menze, F.Kofler, , "Primitive Simultaneous Optimization of Similarity Metrics for Image Registration", Springer - MICCAI BrainLes - LNCS, 14668:57-68, 2024
8. U.Baid, S.Pati, T.M.Kurc, R.Gupta, E.Bremer, S.Abousamra, S.P.Thakur, J.H.Saltz, S.Bakas., "Pan-Cancer Tumor Infiltrating Lymphocyte Detection based on Federated Learning", In IEEE Int. Conf. on Big Data, pp. 7640-7647, 2024
   
   

Abstracts

1. S.Innani, B.Baheti, M.P.Nasrallah, W.R.Bell, S.Bakas, "PATH-39. AI-based identification of glioma IDH mutational status from H&E-stained whole slide images", Neuro-Oncology, 26, Supplement_8, Page viii187, 2024
2. A.Janas, A.Gkampenis, N.Yordanov, P.Fehringer, K.Krantchev, A.W.Moawad, U.Baid, K.E.Link, Y.S.Velichko, D.LaBella, F.Kofler, E.Calabrese, U.Shafique, G.Conte, R.Saluja, N.H.Tahon, N.Maleki, A.Abayazeed, S.Aneja, A.Nada, H.Li, M.Foltyn, S.Bakas, J.Rudie, BraTS-METS Challenge 2023 Group, M.Aboian, , "A novel approach concerning medical education on AI and ML through the ASNR MICCAI BraTS 2023 brain metastases challenge", Neuro-Oncology, 26(Suppl_5):v55, 2024
3. H.Akbari, S.Mohan, A.F.Kazerooni, S.Rathore, M.Bilello, C.Sako, J.Garcia, C.Jiang, F.Liu, M.Berger, S.Brem, S.Bakas, E.Mamourian, A.Pepin, P.James, J.Dorsey, A.Singh, D.Parker, R.Verma, Q.Cao, R.T.Shinohara, S.J.Bagley, A.Desai, D.M.O’Rourke, M.Nasrallah, M.Alonso-Basanta, B.-K.K.Teo, G.Kurtz, G.Shukla, R.A.Lustig, C.Davatzikos,, "AI-Guided Personalized Precision Radiation Therapy With Targeted Dose Esalation for Newly Diagnosed Glioblastoma: A Matched-Control Study", Neuro-Oncology, 26(Suppl_8):viii103-viii103, 2024
4. S.Mohan, J.Garcia, H.Akbari, S.Kwak, K.Baik, M.Shalaby, Y.Matsumoto, S.Bakas, P.Kamel, C.Tippareddy, C.Badve, M.Lee, J.Barnholtz-Sloan, A.Sloan, A.Chakravarti, J.Palmer, A.Dicker, A.Flanders, W.Shi, R.Jain, P.LaMontagne, D.Marcus, A.Sotiras, C.Balana, J.Capellades, J.Puig, S.Cepeda, A.L.D.Stefano, B.Wiestler, G.Woodworth, D.ORourke, M.Nasrallah, C.Davatzikos,, "Multi-Institutional Validation of an AI-based Model for Prediction of Tumor Infiltration and Future Recurrence in Patients with Glioblastoma: Results from the ReSPOND Consortium", Neuro-Oncology, 26(Suppl_8):viii205-viii206, 2024
5. J.Guo, A.Fathi-Kazerooni, E.Toorens, H.Akbari, F.Yu, Y.Matsumoto, C.Sako, E.Mamourian, R.Shinohara, C.Koumenis, I.Verginadis, S.Bagley, J.Morrissette, Z.Binder, S.Brem, S.Mohan, R.Lustig, D.O’Rourke, T.Ganguly, S.Bakas, M.Aboian, M.Nasrallah, C.Davatzikos,, "Subtyping Glioblastoma from Joint Clustering of Imaging and Genomic Data", Neuro-Oncology, 26(Suppl_8):viii209-viii209, 2024
6. S.Thakur, S.Faghani, M.Moassefi, U.Baid, V.Chung, S.Pati, S.Innani, B.Baheti, J.Albrecht, A.Karargyris, H.Kassem, M.Nasrallah, J.Ahrendsen, V.Barresi, M.Gubbiotti, G.Lopez, C.-H.Lucas, M.Miller, L.Cooper, J.Huse, W.R.Bell, S.Bakas, "BraTS-Path: Assessing Heterogenenous Histopathologic Regions in Glioblastoma", Neuro-Oncology, 26(Suppl_8):viii312-viii312, 2024

Journal Manuscripts

1. 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

2. 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.

3. 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

4. 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

5. 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.

6. 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

7. 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.

8. 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.

9. 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.\

10. 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.

11. 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.

12. 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.

13. 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.

14. 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.

15. 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.

Full-length peer-reviewed conference papers

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]

Abstracts

1. 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.

2. 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]

3. 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)

4. 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.

5. 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.

6. S.Pati, S.Bakas, “Federated Learning and Reproducibility in Healthcare”, Proceedings of the Dagstuhl Seminar Series, 2023

7. 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

8. 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

Book chapter

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.

Citable data repositories

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

E-books

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)