Peer-Reviewed Publication
Bioengineering (Basel)2025;12(11)October 26, 2025Journal Article

A Community Benchmark for the Automated Segmentation of Pediatric Neuroblastoma on Multi-Modal MRI: Design and Results of the SPPIN Challenge at MICCAI 2023.

Myrthe A D Buser1, Dominique C Simons1, Matthijs Fitski1, Marc H W A Wijnen1, Annemieke S Littooij1,2, Annemiek H Ter Brugge1, Iris N Vos3, Markus H A Janse3, Mathijs de Boer3, Rens Ter Maat3, Junya Sato4, Shoji Kido4, Satoshi Kondo5, Satoshi Kasai6, Marek Wodzinski7,8, Henning Müller8,9, Jin Ye10, Junjun He10, Yannick Kirchhoff11, Maximilian R Rokkus11, Gao Haokai12, Matías Fernández-Patón13, Diana Veiga-Canuto13, David G Ellis14, Michele Aizenberg14, Bas H M van der Velden3,15, Hugo Kuijf3, Alberto de Luca3, Alida F W van der Steeg1
1Princess Máxima Center for Pediatric Oncology, 3584 CS Utrecht, The Netherlands.
2Department of Radiology, University Medical Center Utrecht, 3584 EA Utrecht, The Netherlands.
3Image Sciences Institute, University Medical Center Utrecht, Utrecht University, 3508 GA Utrecht, The Netherlands.
4Department of Artificial Intelligence in Diagnostic Radiology, Osaka University Graduate School of Medicine, Osaka 545-8585, Japan.
5Department of Sciences and Informatics, Muroran Institute of Technology, Hokkaido 050-8585, Japan.
6Department of Intelligent Information Engineering, Fujita Health University, Aichi 470-1192, Japan.
7Department of Measurement and Electronics, University of Krakow, 30-059 Krakow, Poland.
8Institute of Informatics, HES-SO, 3960 Sierre, Switzerland.
9Department of Radiology and Informatics, University of Geneva, 1211 Geneva, Switzerland.
10Shanghai Artificial Intelligence Laboratory, Shanghai 200232, China.
11Cancer Research Center, 69120 Heidelberg, Germany.
12School of Computer Science, South China Normal University, Guangzhou 510631, China.
13La Fe Health Research Institute, 46026 Valencia, Spain.
14University of Nebraska Medical Center, Omaha, NE 68198, USA.
15Wageningen Food Safety Research, 6708 WB Wageningen, The Netherlands.

Abstract

Surgery plays a key role in treating neuroblastoma. To assist surgical planning, anatomical 3D models derived from the segmentation of anatomical structures on MRI scans are often used. Automation using deep learning can make segmentations less time-consuming and more reliable. We organized the Surgical Planning in PedIatric Neuroblastoma (SPPIN) challenge, to stimulate developments and benchmarki…

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