AutoPET Dataset
Dataset - autoPET - Grand Challenge
CT as well as PET data are provided as 3D volumes consisting of stacks of axial slices. Data provided as part of this challenge consists of whole-body ...
Description - autoPET - Grand Challenge
To promote research on machine learning-based automated tumor lesion segmentation on whole-body FDG-PET/CT data we host the autoPET challenge.
AutoPET Dataset - Papers With Code
A whole-body FDG-PET/CT dataset with manually annotated tumor lesions (FDG-PET-CT-Lesions) 1014 studies (900 patients)
autoPET Challenge 2022 - ESHIᴹᵀ - eshi-society.org
The task is to develop a machine-learning algorithm for accurate lesion segmentation of whole-body FDG-PET/CT while avoiding false positives (brain, bladder, ...
FDG-PET-CT-LESIONS - The Cancer Imaging Archive (TCIA)
FDG-PET-CT-Lesions | A whole-body FDG-PET/CT dataset with manually annotated tumor lesions ... autopet.grand-challenge.org/. Data: The anonymized ...
repository for autoPET machine lerning challenge - GitHub
repository for autoPET machine lerning challenge. Contribute to lab-midas/autoPET development by creating an account on GitHub.
AutoPET Challenge: Tumour Synthesis for Data Augmentation - arXiv
Title:AutoPET Challenge: Tumour Synthesis for Data Augmentation ... Abstract:Accurate lesion segmentation in whole-body PET/CT scans is crucial ...
Results from the autoPET challenge on fully automated lesion ...
The mission of the autoPET challenge is to motivate research on automated PET/CT image analysis, to provide a platform for algorithm comparison ...
AutoPET Challenge 2023: Sliding Window-based Optimization of U ...
Implemented in one code library.
AutoPET Challenge: Tumour Synthesis for Data Augmentation - arXiv
In this paper, we explore the potential of leveraging the deep prior from a generative model to serve as a data augmenter for automated lesion segmentation in ...
alexanderjaus/autopet3_datadiet - GitHub
Welcome to the autoPET III submission Data Diet: Can Trimming PET/CT Datasets Enhance Lesion Segmentation? This project investigates the impact of reducing ...
A whole-body FDG-PET/CT dataset with manually annotated tumor ...
... autoPET MICCAI 2022 competition: https://autopet.grand-challenge.org/. Data: The anonymized publication of data was approved by the local ...
Large-scale transfer of lesion segmentations from PET to CT
In this work, the autoPET Challenge dataset was used. The autoPET Chal- lenges contain PET/CT image datasets and lesion masks based on PET masks. There are ...
[PDF] AutoPET Challenge: Combining nn-Unet with Swin UNETR ...
An ensemble of two state-of-the-art segmentation models, the nn-Unet and the Swin UNETR, augmented by a maximum intensity projection classifier that acts ...
AutoPET News March 8th:The new autoPET-II challenge is now online! September ... Please see the updated Dataset page. Publication of the database ...
AutoPET Challenge 2023: Sliding Window-based Optimization of U ...
Tumor segmentation in medical imaging is crucial and relies on precise delineation. Fluorodeoxyglucose Positron-Emission Tomography (FDG-PET) is widely used ...
AutoPET Challenge 2022 - arxiv-sanity
It allows for automated segmentation of potential lesions. We evaluate the proposed method in the context of AutoPet Challenge, which measures the lesion ...
AutoPET III Challenge: PET/CT Semantic Segmentation - AIModels.fyi
... AutoPET III challenge. The first stage utilized a DynUNet model for ... dataset was split into 80% training and 20% validation ...
Automated Lesion Segmentation in Whole-Body PET/CT - Zenodo
... dataset. This dataset introduces a new tracer, Prostate ... In the first run of the autoPET challenge (AutoPET I at MICCAI 2022) ...
Towards fully automated lesion segmentation in oncologic PET/CT ...
We describe the results of the autoPET challenge, a biomedical image analysis challenge aimed to ... A whole-body FDG-PET/CT Dataset with manually ...