M. M. Amaan Valiuddin

According to our database, M. M. Amaan Valiuddin authored at least 7 papers between 2021 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of five.

2023

Investigating and Improving Latent Density Segmentation Models for Aleatoric Uncertainty Quantification in Medical Imaging.

M. M. Amaan Valiuddin, Christiaan G. A. Viviers, Ruud J. G. van Sloun, Peter H. N. de With, Fons van der Sommen

CoRR, 2023

Probabilistic 3D segmentation for aleatoric uncertainty quantification in full 3D medical data.

Christiaan G. A. Viviers, M. M. Amaan Valiuddin, Peter H. N. de With, Fons van der Sommen

Proceedings of the Medical Imaging 2023: Computer-Aided Diagnosis, 2023

Segmentation-based Assessment of Tumor-Vessel Involvement for Surgical Resectability Prediction of Pancreatic Ductal Adenocarcinoma.

Christiaan G. A. Viviers, Mark Ramaekers, M. M. Amaan Valiuddin, Terese Hellström, Nick Tasios, John van der Ven, Igor Jacobs, Lotte Ewals, Joost Nederend, Peter H. N. de With, Misha Luyer, Fons van der Sommen

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022

Efficient Out-of-Distribution Detection of Melanoma with Wavelet-Based Normalizing Flows.

M. M. Amaan Valiuddin, Christiaan G. A. Viviers, Ruud J. G. van Sloun, Peter H. N. de With, Fons van der Sommen

Proceedings of the Cancer Prevention Through Early Detection, 2022

2021

Improving Aleatoric Uncertainty Quantification in Multi-Annotated Medical ImageSegmentation with Normalizing Flows.

M. M. Amaan Valiuddin, Christiaan G. A. Viviers, Ruud J. G. van Sloun, Peter H. N. de With, Fons van der Sommen

CoRR, 2021

Out-of-Distribution Detection of Melanoma using Normalizing Flows.

M. M. Amaan Valiuddin, Christiaan G. A. Viviers

CoRR, 2021

Improving Aleatoric Uncertainty Quantification in Multi-annotated Medical Image Segmentation with Normalizing Flows.

M. M. Amaan Valiuddin, Christiaan G. A. Viviers, Ruud J. G. van Sloun, Peter H. N. de With, Fons van der Sommen

Proceedings of the Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Perinatal Imaging, Placental and Preterm Image Analysis, 2021