Research graph
References from RAC-Net: Interpretable Medical Small Target Segmentation Network With X-Ray Radiation Attenuation Characterization. Local targets link to admitted publications; unresolved targets remain external evidence.
10.1109/tmi.2018.2872031
10.1109/tmi.2018.2872031 · External reference
10.1109/iembs.2011.6092092
10.1109/iembs.2011.6092092 · External reference
10.1109/tmi.2023.3264513
10.1109/tmi.2023.3264513 · External reference
10.1145/3767748
10.1145/3767748 · External reference
10.1145/3664647.3681033
10.1145/3664647.3681033 · External reference
10.1016/j.media.2020.101874
10.1016/j.media.2020.101874 · External reference
10.1109/tmi.2019.2903562
10.1109/tmi.2019.2903562 · External reference
10.1016/j.neunet.2023.11.034
10.1016/j.neunet.2023.11.034 · External reference
10.1016/j.asoc.2023.110683
10.1016/j.asoc.2023.110683 · External reference
10.1016/j.ins.2023.119005
10.1016/j.ins.2023.119005 · External reference
10.1016/j.media.2023.102929
10.1016/j.media.2023.102929 · External reference
10.1109/tmi.2024.3398728
10.1109/tmi.2024.3398728 · External reference
10.1109/tmi.2021.3111679
10.1109/tmi.2021.3111679 · External reference
10.1109/tmi.2020.3001036
10.1109/tmi.2020.3001036 · External reference
10.1109/tmi.2015.2398818
10.1109/tmi.2015.2398818 · External reference
10.1109/tmi.2019.2923601
10.1109/tmi.2019.2923601 · External reference
10.1007/s11548-017-1619-0
10.1007/s11548-017-1619-0 · External reference
10.1007/978-3-030-32239-7_30
10.1007/978-3-030-32239-7_30 · External reference
10.1109/jbhi.2022.3186275
10.1109/jbhi.2022.3186275 · External reference
10.1109/jbhi.2021.3089201
10.1109/jbhi.2021.3089201 · External reference
10.1109/tcbb.2022.3188148
10.1109/tcbb.2022.3188148 · External reference
10.1109/jbhi.2022.3163352
10.1109/jbhi.2022.3163352 · External reference
10.1109/tim.2022.3193188
10.1109/tim.2022.3193188 · External reference
10.1007/978-3-031-25066-8_9
10.1007/978-3-031-25066-8_9 · External reference
10.1109/tpami.2024.3434435
10.1109/tpami.2024.3434435 · External reference
10.1038/s41598-025-94437-9
10.1038/s41598-025-94437-9 · External reference
10.2214/ajr.18.19704
10.2214/ajr.18.19704 · External reference
10.1186/s12879-015-0944-6
10.1186/s12879-015-0944-6 · External reference
10.1016/s0033-8389(05)70030-0
10.1016/s0033-8389(05)70030-0 · External reference
10.1109/tpami.2022.3211171
10.1109/tpami.2022.3211171 · External reference
10.1016/j.compbiomed.2023.106985
10.1016/j.compbiomed.2023.106985 · External reference
10.1148/radiographics.18.1.9460114
10.1148/radiographics.18.1.9460114 · External reference
10.1038/s43586-021-00015-4
10.1038/s43586-021-00015-4 · External reference
10.1109/tpami.2014.2345390
10.1109/tpami.2014.2345390 · External reference
10.2967/jnumed.125.270168
10.2967/jnumed.125.270168 · External reference
10.1118/1.594678
10.1118/1.594678 · External reference
10.1109/cvpr.2015.7298965
10.1109/cvpr.2015.7298965 · External reference
10.1007/978-3-319-24574-4_28
10.1007/978-3-319-24574-4_28 · External reference
10.1007/978-3-030-00889-5_1
10.1007/978-3-030-00889-5_1 · External reference
Attention U-Net: Learning where to look for the pancreas
2018 · External reference
10.1109/itme.2018.00080
10.1109/itme.2018.00080 · External reference
Recurrent residual convolutional neural network based on U-Net (R2U-Net) for medical image segmentation
2018 · External reference
10.48550/arxiv.1802.00368
10.48550/arxiv.1802.00368 · External reference
10.1109/cbms49503.2020.00111
10.1109/cbms49503.2020.00111 · External reference
10.1109/tnnls.2022.3159394
10.1109/tnnls.2022.3159394 · External reference
10.1109/cvpr.2018.00813
10.1109/cvpr.2018.00813 · External reference
10.1109/iccv.2019.00069
10.1109/iccv.2019.00069 · External reference
10.1007/978-3-031-16443-9_50
10.1007/978-3-031-16443-9_50 · External reference
10.1109/tmi.2025.3561797
10.1109/tmi.2025.3561797 · External reference
10.1038/s41467-024-44824-z
10.1038/s41467-024-44824-z · External reference
10.1016/j.media.2020.101821
10.1016/j.media.2020.101821 · External reference
10.1016/j.media.2010.05.005
10.1016/j.media.2010.05.005 · External reference
10.1016/j.media.2017.06.015
10.1016/j.media.2017.06.015 · External reference
10.1109/bibm55620.2022.9995040
10.1109/bibm55620.2022.9995040 · External reference
10.1007/s00521-022-07859-1
10.1007/s00521-022-07859-1 · External reference
10.1016/j.compbiomed.2023.107378
10.1016/j.compbiomed.2023.107378 · External reference
10.1109/tmi.2018.2837502
10.1109/tmi.2018.2837502 · External reference
10.1109/tip.2024.3482175
10.1109/tip.2024.3482175 · External reference
10.1109/tip.2019.2919937
10.1109/tip.2019.2919937 · External reference
10.1109/tpami.2023.3322735
10.1109/tpami.2023.3322735 · External reference
10.1609/aaai.v36i3.20144
10.1609/aaai.v36i3.20144 · External reference
10.1016/j.neunet.2019.08.025
10.1016/j.neunet.2019.08.025 · External reference
10.1007/978-3-031-43898-1_66
10.1007/978-3-031-43898-1_66 · External reference
10.1109/42.845178
10.1109/42.845178 · External reference
10.1109/tbme.2016.2535311
10.1109/tbme.2016.2535311 · External reference
10.1167/iovs.08-3018
10.1167/iovs.08-3018 · External reference
The KiTS19 challenge data: 300 kidney tumor cases with clinical context, CT semantic segmentations, and surgical outcomes
2019 · External reference
