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Zaigham Saghir
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2020 – today
- 2023
- [c3]Joeran Bosma, Dre Peeters, Natália Alves, Anindo Saha, Zaigham Saghir, Colin Jacobs, Henkjan Huisman:
Reproducibility of Training Deep Learning Models for Medical Image Analysis. MIDL 2023: 1269-1287 - 2021
- [i2]Antonio Garcia-Uceda Juarez, Raghavendra Selvan, Zaigham Saghir, Harm A. W. M. Tiddens, Marleen de Bruijne:
Automatic airway segmentation from Computed Tomography using robust and efficient 3-D convolutional neural networks. CoRR abs/2103.16328 (2021) - 2020
- [j1]Ruwan B. Tennakoon, Gerda Bortsova, Silas Nyboe Ørting, Amirali K. Gostar, Mathilde M. W. Wille, Zaigham Saghir, Reza Hoseinnezhad, Marleen de Bruijne, Alireza Bab-Hadiashar:
Classification of Volumetric Images Using Multi-Instance Learning and Extreme Value Theorem. IEEE Trans. Medical Imaging 39(4): 854-865 (2020)
2010 – 2019
- 2019
- [c2]Antonio Garcia-Uceda Juarez, Raghavendra Selvan, Zaigham Saghir, Marleen de Bruijne:
A Joint 3D UNet-Graph Neural Network-Based Method for Airway Segmentation from Chest CTs. MLMI@MICCAI 2019: 583-591 - [i1]Antonio Garcia-Uceda Juarez, Raghavendra Selvan, Zaigham Saghir, Marleen de Bruijne:
A joint 3D UNet-Graph Neural Network-based method for Airway Segmentation from chest CTs. CoRR abs/1908.08588 (2019) - 2011
- [c1]Jens Petersen, Mads Nielsen, Pechin Lo, Zaigham Saghir, Asger Dirksen, Marleen de Bruijne:
Optimal Graph Based Segmentation Using Flow Lines with Application to Airway Wall Segmentation. IPMI 2011: 49-60
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