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Specification of the terms of data use of the TopCoW 2024 challenge released data:
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* Following the definitions of "https://opendata.swiss/en/terms-of-use" (retrieved in April 2024) on open data use, the following license is chosen:
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"Terms of data use:
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Open use. Must provide the source. Use for commercial purposes requires permission of the data owner.
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* You may use this dataset for non-commercial purposes.
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* You may use this dataset for commercial purposes, but you must seek prior permission from the data owner.
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* You must provide the source (author, title and link to the dataset)."
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Data owner is University Hospital of Zurich, Department of Neurology, Rämistrasse 100, 8091 Zürich (USZ),
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the resulting publication or pre-print of the TopCoW challenge – to which USZ is a co-author – will serve as reference for data citation.
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###############################################
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TopCoW 2024 MICCAI Challenge Data Release
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Website: https://topcow24.grand-challenge.org/
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_________________________
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< Welcome to TopCoW 2024! >
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-------------------------
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\ ^__^
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\ (oo)\_______
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(__)\ )\/\
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||----w |
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|| ||
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###############################################
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1. Overview
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This public dataset is released for the
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TopCoW (Topology-Aware Anatomical Segmentation of the Circle of Willis for CTA and MRA) challenge,
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to be held with the Medical Image Computing and Computer Assisted Intervention (MICCAI) conference in October 2024.
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2. Data Usage License
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Following the definitions of "https://opendata.swiss/en/terms-of-use" on open data use,
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the following license is chosen:
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"Terms of data use:
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Open use. Must provide the source. Use for commercial purposes requires permission of the data owner.
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* You may use this dataset for non-commercial purposes.
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* You may use this dataset for commercial purposes, but you must seek prior permission from the data owner.
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* You must provide the source (author, title and link to the dataset)."
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By downloading the data, you agree with the license terms.
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For more information, please refer to the "License.txt" file in the same release folder.
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3. Contents of Data
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The training data consist of
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- 250 (=125 pairs) CTA and MRA for TopCoW 2024 challenge
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- voxel annotations for CoW multi-class segmentation
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- bounding box annotations for CoW object detection
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- edge list annotations for CoW graph classification
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The training (Tr) data folder has the following sub-folders:
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* `imagesTr`: Angiographic scans in nifti format, 16-bit signed. LPS+ orientation
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* The nifti filenames are saved with schema: `topcow_{modality}_{pat_id}_0000.nii.gz`
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* `modality`: `mr` for MRA, `ct` for CTA
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* `pat_id`: patient ID, `001`, `002`, ...
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* `cow_seg_labelsTr`: Multi-class segmentation mask nifti with CoW anatomical labels
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* Voxel values for different CoW vessel segments:
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* 0: Background, 1: BA, 2: R-PCA, 3: L-PCA, 4: R-ICA, 5: R-MCA, 6: L-ICA, 7: L-MCA, 8: R-Pcom, 9: L-Pcom, 10: Acom,11: R-ACA, 12: L-ACA, 15: 3rd-A2
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* `roi_loc_labelsTr`: Size and location info for the CoW region of interest (ROI) i.e. the 3D bounding box:
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* Text file containing the size and location of the 3D bounding box info
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* Size = number of pixels along the x, y, z axis
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* Location = coordinate of the x-min, y-min, z-min (0-indexed)
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* `antpos_edges_labelsTr`: Edge list of anterior and posterior edges of the CoW graph
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* Yml file indicating the presence of edges (0: absent, 1: present)
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* 4 edges for `anterior` part, roughly from left to right:
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* L-A1
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* Acom
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* 3rd-A2
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* R-A1
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* 4 edges for `posterior` part, roughly from left to right:
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* L-Pcom
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* L-P1
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* R-P1
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* R-Pcom
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We also release 10 (=5 pairs) CTA and MRA from TopCoW challenge in folder `imagesVal` but without the accompanying annotations.
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The small validation set is intended to validate the docker submission technically and not counted towards the ranking.
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4. Citation
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If you use TopCoW challenge data in your work, please cite our challenge pre-print:
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@misc{topcowchallenge,
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title={Benchmarking the CoW with the TopCoW Challenge: Topology-Aware Anatomical Segmentation of the Circle of Willis for CTA and MRA},
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author={Kaiyuan Yang and Fabio Musio and Yihui Ma and Norman Juchler and Johannes C. Paetzold and Rami Al-Maskari and Luciano Höher and Hongwei Bran Li and Ibrahim Ethem Hamamci and Anjany Sekuboyina and Suprosanna Shit and Houjing Huang and Chinmay Prabhakar and Ezequiel de la Rosa and Diana Waldmannstetter and Florian Kofler and Fernando Navarro and Martin Menten and Ivan Ezhov and Daniel Rueckert and Iris Vos and Ynte Ruigrok and Birgitta Velthuis and Hugo Kuijf and Julien Hämmerli and Catherine Wurster and Philippe Bijlenga and Laura Westphal and Jeroen Bisschop and Elisa Colombo and Hakim Baazaoui and Andrew Makmur and James Hallinan and Bene Wiestler and Jan S. Kirschke and Roland Wiest and Emmanuel Montagnon and Laurent Letourneau-Guillon and Adrian Galdran and Francesco Galati and Daniele Falcetta and Maria A. Zuluaga and Chaolong Lin and Haoran Zhao and Zehan Zhang and Sinyoung Ra and Jongyun Hwang and Hyunjin Park and Junqiang Chen and Marek Wodzinski and Henning Müller and Pengcheng Shi and Wei Liu and Ting Ma and Cansu Yalçin and Rachika E. Hamadache and Joaquim Salvi and Xavier Llado and Uma Maria Lal-Trehan Estrada and Valeriia Abramova and Luca Giancardo and Arnau Oliver and Jialu Liu and Haibin Huang and Yue Cui and Zehang Lin and Yusheng Liu and Shunzhi Zhu and Tatsat R. Patel and Vincent M. Tutino and Maysam Orouskhani and Huayu Wang and Mahmud Mossa-Basha and Chengcheng Zhu and Maximilian R. Rokuss and Yannick Kirchhoff and Nico Disch and Julius Holzschuh and Fabian Isensee and Klaus Maier-Hein and Yuki Sato and Sven Hirsch and Susanne Wegener and Bjoern Menze},
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