Kaczmarska, MartaMajek, Karol2023-09-222023-09-222023Kaczmarska M., Majek K., Loss Function Influence on Uncertainty Estimation for White Matter Lesions 3D Segmentation in a Shifted Domain Setting. W: Progress in Polish Artificial Intelligence Research 4, Wojciechowski A. (Ed.), Lipiński P. (Ed.)., Seria: Monografie Politechniki Łódzkiej Nr. 2437, Wydawnictwo Politechniki Łódzkiej, Łódź 2023, s. 245-250, ISBN 978-83-66741-92-8, doi: 10.34658/9788366741928.39.978-83-66741-92-8http://hdl.handle.net/11652/4815https://doi.org/10.34658/9788366741928.39The aim of this study is to address the problem of distributional shift for white matter Multiple Sclerosis lesion segmentation models. The impact of loss function on models performance and uncertainty estimation is evaluated. The evaluation is performed on two in-domain and one out-ofdomain dataset consisting of 3D FLAIR Magnetic Resonance images. Our experiments show that application of segmentation losses (eg. Dice) translate into reduced models robustness and poorer uncertainty estimation compared with classification losses (eg. CE). The source code is publicly available.enDla wszystkich w zakresie dozwolonego użytkuFair use conditionwhite matter multiple sclerosis lesionsmultiple sclerosis3D segmentationmagnetic resonance imagingzmiany w istocie białej w stwardnieniu rozsianymstwardnienie rozsianesegmentacja 3Drezonans magnetycznyRozdział - monografiaLicencja PŁLUT License10.34658/9788366741928.39