Auto-WCEBleedGen Challenge Version V2 Challenge: ICIP 2024

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Auto-WCEBleedGen Challenge Version V2 Challenge: ICIP 2024


Auto-WCEBleedGen Challenge is an second version of a previous challenge that focused on automatic detection and classification of bleeding and non-bleeding frames. It this current version the organisers proposed to focus also on automatic classification of bleeding and non-bleeding frames by extending it also to further detection and segmentation of bleeding region in that frame. The dataset was updated in accordance to this purpose.

Gastrointestinal (GI) bleeding is a medical condition characterized by bleeding in the GI tract, which circumscribes oesophagus, stomach, small intestine, large intestine (colon), rectum, and anus. Since blood flows into the GI tract, a cascade of risks emerges, ranging from immediate dangers to potential long-term consequences. Excessive blood loss from GI bleeding may lead to a drop in blood pressure, reduced oxygen delivery to organs and tissues, and potentially life-threatening organ dysfunction.

According to World Health Organization (WHO), GI bleeding is responsible for approximately 300,000 deaths every year globally. These statistics serve as a catalyst for research, propelling innovative treatment modalities and diagnostic advancements aimed at mitigating the dangers posed by GI bleeding. In last decade, the availability of advanced diagnostic innovations like Wireless Capsule Endoscopy (WCE) has led to better understanding of the GI bleeding in GI tract. The disposable capsule-shaped device travels inside the GI tract via peristalsis and comprises of an optical dome, a battery, an illuminator, an imaging sensor, and a radio-frequency transmitter. During 8-12 hours of WCE procedure, a video of the GI tract trajectory is recorded on a device attached to the patient’s belt which produces about 57,000-1,00,000 frames; analysed posterior by experienced gastroenterologists...

Visit the Challenge website for details and more information!


Technical Committee: Bio Imaging and Signal Processing


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