Endoscopy Disease Detection and Segmentation (EDD2020)

Submission Dates:
01/15/2020 to 03/06/2020
Citation Author(s):
Sharib
Ali
University of Oxford, Big Data Institute, Department of Engineering Science
Barbara
Braden
University of Oxford, Translational Gastroenterology Unit, Nuffield Department of Medicine, Experimental Medicine Div., John Radcliffe
Dominique
Lamarque
Université de Versailles St-Quentin en Yvelines, Hôpital Ambroise Paré
Stefano
Realdon
Instituto Onclologico Veneto, IOV-IRCCS, Padova, Italy
Adam
Bailey
University of Oxford, Translational Gastroenterology Unit, Nuffield Department of Medicine, Experimental Medicine Div., John Radcliffe
Renato
Cannizzaro
CRO Centro Riferimento Oncologico IRCCS Aviano Italy
Noha
Ghatwary
University of Lincoln, UK
Jens
Rittscher
University of Oxford, Big Data Institute, Department of Engineering Science
Christian
Daul
CRAN UMR 7039, University of Lorraine, CNRS, Nancy, France
James
East
University of Oxford, Translational Gastroenterology Unit, Nuffield Department of Medicine, Experimental Medicine Div., John Radcliffe
Submitted by:
sharib ali
Last updated:
Sat, 02/27/2021 - 05:11
DOI:
10.21227/f8xg-wb80
Data Format:
Links:
License:
Creative Commons Attribution

Abstract 

Endoscopy is a widely used clinical procedure for the early detection of cancers in hollow-organs such as oesophagus, stomach, and colon. Computer-assisted methods for accurate and temporally consistent localisation and segmentation of diseased region-of-interests enable precise quantification and mapping of lesions from clinical endoscopy videos which is critical for monitoring and surgical planning. Innovations have the potential to improve current medical practices and refine healthcare systems worldwide. However, well-annotated, representative publically-available datasets for disease detection for assessing reproducibility and facilitating standardised comparison of methods is still lacking. Many methods to detect diseased regions in endoscopy have been proposed however these have primarily focussed on the task of polyp detection in the gastrointestinal tract with demonstration on datasets acquired from at most a few data centres and single modality imaging, most commonly white light. Here, we present our multi-class disease detection and segmentation challenge in clinical endoscopy. With this sub-challenge we aim to establish a comprehensive dataset to benchmark algorithms for disease detection. Specifically we aim to assess: Precise spatio-temporal localisation of disease regions using bounding boxes and exact pixel-level segmentation. Clinical applicability by assessing the online sequential for real-time monitoring and offline performance of algorithms for improved accuracy and better quantitative reporting. Participants will be provided with a set of annotated dataset labelled by medical experts and experienced doctoral/post-doctoral researchers with frames from 5 different international centres and multi organs targeting multiple populations and varied endoscopy video modalities associated with pre-malignant and diseased regions as follows: Organ 1: Colon-rectal, associated disease: polyp, cancer Organ 2: Oesophagus, associated disease: Barrett’s, dysplasia and cancer Organ 3: Stomach and duodenum, associated disease: pyloric inflammation, dysplasia, cancer

Comments

Compitition data

where can we download the data?

I submitted the data application, more than ten days later, why haven't I received an email? and where can I download the data? Plese 

I submitted the data application, more than ten days later, why haven't I received an email? and where can I download the data? Plese 

I submitted the data application, more than ten days later, why haven't I received an email? and where can I download the data? Plese 

I submitted the data application, more than ten days later, why haven't I received an email? and where can I download the data? Plese 

Dear all,

 

Our apologies. We have now released this data without requiring anyone to login and request. However, we suggest you to download it from our challenge website https://edd2020.grand-challenge.org, where we have provided a python script to download this. 

 

Many thanks,

 

Best wishes,

Sharib 

Hi, it seems the python file is no longer available on the website.

Is there any place to download the dataset now?

I also can’t download the training data of Endoscopy Disease Detection and Segmentation (EDD2020) either on the official website or here.
Is the dataset still available?

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