5-MICC at ICIP 2021 - Vote for the Clip
5-MICC Contest at ICIP 2021: Vote for the Clip
IEEE SPS 5-Minute Video Clip Contest at ICIP 2021:
Automatic Medical Image Diagnosis
Voting period has closed!
The IEEE Signal Processing Society is excited to announce the finalists of the first SPS 5-Minute Video Clip Contest!
The voting platform is now open, and you can help support the final three teams by voting for your favorite video! Cast your vote by 11:59 PM (ET) on Monday, 20 September 2021. You may only vote once.
Voting is simple! To vote, please follow the steps below:
- View the three videos below.
- Select "vote" located under the video you choose to vote for.
- Enter your name, affiliation, and email address
- Click "submit."
(Collected information is used to aid in as part of the evaluation process and to monitor duplicate entries and fraudulent voting. Personal data will not be stored.)
This year’s topic, Automatic Medical Image Diagnosis, asked students to explore the automatic detection, identification, classification, or discrimination of various medical conditions, components, and aspects is essential in today's medical practices, enabling for example detailed and high-precision diagnosis to be possible. In various medical imaging applications such as dermoscopic, fundoscopic, and endoscopic imaging, automatic processing of abnormalities and aberrations greatly help physicians in the diagnosis process. Students were also welcome to submit “open topic” videos about subjects besides beamforming.
Finalists Announced
| Grand Prize: $5,000 Video Title: Automatic medical diagnosis and image quality enhancement for video otoscopy examination Universidad Tecnica Federico Santa Maria Supervisor: Prof. Fernando Auat Cheein Students: Paula Amigo, Daniela Garrido, Matias Talamilla, Michelle Viscaino |
| First Runner-Up: $2,500 Video Title: Neural Networks and Cancer Detection in Tissue Scans Masaryk University Supervisor: Tomáš Brázdil Students: Vojtěch Krajňanský, Andrej Kubanda, Jiří Horák, Jakub Hruška |
| Second Runner-Up: $1,500 Video Title: Deep learning for COVID-19 diagnosis A to Z Concordia University Supervisor: Arash Mohammadi Students: Parnian Afshar, Mohamed Elsagh, Megan Walbaum, Chit Chit M.C. Zaw, Ya Ling Wu, Marian Maksimo |
Voting Platform (Closed)
Finalist Videos
If you are unable to view videos via YouTube, please access them directly via the links below:
1. Click on the links below:
- Grand Prize: Video Title: Automatic medical diagnosis and image quality enhancement for video otoscopy examination
- First Runner-Up: Video Title: Neural Networks and Cancer Detection in Tissue Scans
- Second Runner-Up: Video Title: Deep learning for COVID-19 diagnosis A to Z
2. View all three videos.
3. Return to the current page and cast your vote using the platform above.
