ROOD-MRI: Benchmarking the robustness of deep learning segmentation models to out-of-distribution and corrupted data in MRI von Boone, Lyndon, Biparva, Mahdi, Mojiri Forooshani, Parisa, Ramirez, Joel, Masellis, Mario, Bartha, Robert, Symons, Sean, Strother, Stephen, Black, Sandra E., Heyn, Chris, Martel, Anne L., Swartz, Richard H., Goubran, Maged

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Progressive White Matter Injury in Preclinical Dutch Cerebral Amyloid Angiopathy von Shirzadi, Zahra, Yau, Wai‐Ying W., Schultz, Stephanie A., Schultz, Aaron P., Scott, Matthew R., Goubran, Maged, Mojiri‐Forooshani, Parisa, Joseph‐Mathurin, Nelly, Kantarci, Kejal, Preboske, Greg, Wermer, Marieke J. H., Jack, Clifford, Benzinger, Tammie, Taddei, Kevin, Sohrabi, Hamid R., Sperling, Reisa A., Johnson, Keith A., Bateman, Randall J., Martins, Ralph N., Greenberg, Steven M., Chhatwal, Jasmeer P.

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Deep Bayesian networks for uncertainty estimation and adversarial resistance of white matter hyperintensity segmentation von Mojiri Forooshani, Parisa, Biparva, Mahdi, Ntiri, Emmanuel E., Ramirez, Joel, Boone, Lyndon, Holmes, Melissa F., Adamo, Sabrina, Gao, Fuqiang, Ozzoude, Miracle, Scott, Christopher J. M., Dowlatshahi, Dar, Lawrence‐Dewar, Jane M., Kwan, Donna, Lang, Anthony E., Marcotte, Karine, Leonard, Carol, Rochon, Elizabeth, Heyn, Chris, Bartha, Robert, Strother, Stephen, Tardif, Jean‐Claude, Symons, Sean, Masellis, Mario, Swartz, Richard H., Moody, Alan, Black, Sandra E., Goubran, Maged

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DEVELOPING AN ARTIFICIAL INTELLIGENCE (AI) MODEL TO EFFICIENTLY MEASURE ENDOMETRIAL THICKNESS WITHIN ULTRASOUND (US) IMAGES von Mercuri, Natalie, Forooshani, Parisa Mojiri, Qi, Weikai, Fjeldstad, Jullin, Krivoi, Alex, Nayot, Dan

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Cerebrovascular injury markers explain the effect of systemic vascular risk on cognitive decline in older adults with lower amyloid burden von Shirzadi, Zahra, Yau, Wai‐Ying Wendy, Rabin, Jennifer S., Buckley, Rachel F., Properzi, Michael J, Fu, Jessie Fanglu, Hsieh, Stephanie, Thibault, Emma G., Mojiri‐Forooshani, Parisa, Goubran, Maged, MacIntosh, Bradley J., Black, Sandra E., Price, Julie C, Johnson, Keith A., Sperling, Reisa A., Chhatwal, Jasmeer P., Schultz, Aaron P.

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ROOD-MRI: Benchmarking the robustness of deep learning segmentation models to out-of-distribution and corrupted data in MRI von Boone, Lyndon, Biparva, Mahdi, Forooshani, Parisa Mojiri, Ramirez, Joel, Masellis, Mario, Bartha, Robert, Symons, Sean, Strother, Stephen, Black, Sandra E, Heyn, Chris, Martel, Anne L, Swartz, Richard H, Goubran, Maged

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