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Niels van Nistelrooij

nvnistelrooij

  •  Netherlands
  •  Radboud University Medical Center
  •  Oral and Maxillofacial Surgery
Organizations
Statistics
  • Member for 2 years, 10 months
  • 97 challenge submissions
  • 73 algorithms run

Activity Overview

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DRIVE
Challenge User

Develop a system to automatically segment vessels in human retina fundus images.

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RibFrac
Challenge User

Rib Fracture Detection and Classification Challenge: A large-scale benchmark of 660 CT scans with ~5,000 rib fractures (around 80Gb)

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AutoImplant 2021
Challenge User

Second MICCAI Challenge on Automatic Cranial Implant Design (AutoImplant 2021)

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The PI-CAI Challenge
Challenge User

Artificial Intelligence and Radiologists at Prostate Cancer Detection in MRI

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3D Teeth Scan Segmentation and Labeling Challenge MICCAI2022
Challenge User

Computer-aided design (CAD) tools have become increasingly popular in modern dentistry for highly accurate treatment planning. In particular, in orthodontic CAD systems, advanced intraoral scanners (IOSs) are now widely used as they provide precise digital surface models of the dentition. Such models can dramatically help dentists simulate teeth extraction, move, deletion, and rearrangement and therefore ease the prediction of treatment outcomes. Although IOSs are becoming widespread in clinical dental practice, there are only few contributions on teeth segmentation/labeling available in the literature and no publicly available database. A fundamental issue that appears with IOS data is the ability to reliably segment and identify teeth in scanned observations. Teeth segmentation and labelling is difficult as a result of the inherent similarities between teeth shapes as well as their ambiguous positions on jaws.

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DENTEX - MICCAI23
Challenge User

Dental Enumeration and Diagnosis on Panoramic X- rays Challenge

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ToothFairy3: Multi-Class Segmentation in CBCT Volumes
Challenge Editor

ToothFairy3, part of the ODIN2025 challenge cluster at MICCAI2025, advances CBCT segmentation with an expanded 77-class dataset and a new emphasis on computational efficiency. It introduces two tasks: a runtime-aware multi-structure segmentation and a novel interactive track for Inferior Alveolar Canal (IAC) segmentation using minimal user input. The challenge supports the development of both automated and prompt-based interactive AI tools to enhance clinical workflows in dentistry and maxillofacial surgery.

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JawFracNet
Algorithm Editor

Segment mandible and mandibular fractures in head CBCT scan