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Home/Review of the EAD2019 Grand Challenge Workshop at ISBI 2019 in Venice

Review of the EAD2019 Grand Challenge Workshop at ISBI 2019 in Venice

Review kindly submitted by travel grant recipient Refika Sultan DOĞAN

The Endoscopic Artefact Detection challenge (EAD2019) is a great opportunity to share information and meet people who participated in the competition at the IEEE International Symposium on Biomedical Imaging (ISBI). Refika Sultan DOĞAN is with the Biomedical Instrumentation and Signal Analysis Laboratory in Turkey. She applied for this challenge when she was researching her dissertation and joined the workshop of EAD2019 grand challenge. Her B.Sc. was in biomedical engineering from the Erciyes University, Turkey and she is now a Ph.D. student in the Department of Electrical and Computer Engineering (ECE), Biomedical and Biomedical Technologies, Abdullah Gül University, Kayseri, Turkey. She conducts research related to medical image processing, bioinformatics, and cancer genetics with her advisor Bülent YILMAZ, Professor. She traveled to the Endoscopic Artefact Detection Challenge 2019, hosted by Sharib Ali, thanks to a travel grant by MedIAN. She shared with us her experiences on how she found the EAD2019 grand challenge and IEEE International Symposium on Biomedical Imaging while she was in Venice.


“The Endoscopic Artefact Detection challenge (EAD2019) is a great opportunity to share information and meet people who participated in the competition at the IEEE International Symposium on Biomedical Imaging (ISBI). This challenge was great at facilitating the diagnosis and treatment of diseases in hollow organs. Precise detection of specific work such as pixel saturation, motion blur, specular reflections, bubbles, and debris is important for high-quality frame restoration and is important for the realization of reliable computer-aided tools for patient care. Additionally multi-tissue, multi-modal and multi-population as a dataset also made a unique contribution to the literature thanks to this challenge. The intense interest of the participants from all over the world in this competition shows the necessity of such a study. This online challenge is the result of successful and meticulous work. I am thankful to the organization team for their valuable work and contributions. It was a great pleasure to be a part of this competition, to meet and work with such a large and comprehensive data set.

Thanks to the MEDIAN’s support and sponsorship, I had the opportunity to participate in the ISBI in the Italy, Venice and EAD2019 challenge workshop as a travel grant winner. I am grateful to the MEDIAN and those who organized this challenge.

It started with ISBI EAD2019 challenge and continued for 4 days. This symposium provided a wonderful environment to meet new people, exchange information, share our solutions and our algorithms with other diverse collaborators in science and engineering. Another important aspect of this symposium was that it brought together scientists and medical doctors which could lead to new collaborations.

Additionally, the keynote speakers’ world-renowned imaging and clinicians’ conversation was very illuminating. The challenge workshop was especially informative as those participating in the challenge shared their results and methods. It was a unique experience for me to participate in the online challenge and be invited to the challenge workshop.

The IEEE ISBI and EAD2019 challenge workshop allows you to have an opinion on almost every field on biomedical imaging, to debate your thoughts freely and to discuss the points you do not understand, ultimately created an instructive atmosphere for us. I felt lucky to be here in Venice, a UNESCO World Heritage site for this event.

I would like to thank the valuable organization committee of EAD2019 for its invitation, hospitality, and effective communication. I am especially grateful to the valuable MEDIAN team who has been sponsoring me to participate in this symposium and challenge workshop.
Hope to see you in another challenge and symposium!”

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Keywords

AI Applied Machine Learning artefact detection Biomedical image analysis Cell tracking Clinical translation Collaboration conference Deep Learning endoscopy
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