IEEE SPS Video and Image Processing Cup

Sunday, 7 October 2018, 16:30-18:00

The IEEE SPS Video and Image Processing Cup (VIP Cup) student competition, presented by the IEEE Signal Processing Society, gives students the opportunity to work together to solve real-life problems using video and image processing methods. After students submit their work, three final teams are selected to present their work and compete for the grand prize at ICIP 2018!

2018 VIP-CUP Call for Participation

Interested in competing? See the competition guidelines below!

Full details on the VIP CUP website.

While only the final three teams will be competition at ICIP 2018, all are welcome to watch the students present their work during the final competition. Join us and come see the action!

IEEE SPS VIP Cup 2018: Lung Cancer Radiomics-Tumor Region Segmentation

For full competition details, eligibility requirements, and team registration, visit the IEEE Signal Processing Society website.

The volume, variety, and velocity of medical imaging data is exploding, making it impractical for clinicians to properly utilize the available information resources in an efficient fashion. At the same time, interpretation of such large amount of medical imaging data by humans is significantly error prone reducing the possibility of extracting informative data. The ability to process such large amounts of data promises to decipher the un-decoded information within medical images; Develop predictive and prognosis models to design personalized diagnosis; Allow comprehensive study of tumor phenotype, and; Assess tissue heterogeneity for diagnosis of different type of cancers. Recently, there has been a great surge of interest on Radiomics, which refers to the process of extracting and analyzing several semi-quantitative (e.g., attenuation, shape, size, and location) and quantitative features (e.g., wavelet decomposition, histogram, and gray-level intensity) from medical images with the ultimate goal of obtaining predictive or prognostic models. Radiomics workflow, typically, consists of the following four main processing tasks:

  1. Image acquisition/modality;
  2. Image segmentation;
  3. Feature extraction and qualification, and;
  4. Statistical analysis and model building.

The Radiomics features can be extracted from different imaging modalities including Magnetic Resonance Imaging (MRI); Positron Emission Tomography (PET), and; Computed Tomography (CT), therefore, have the capability of providing complementary information for clinical decision making in clinical oncology.

Recent developments and advancement in Signal Processing and Machine Learning solutions have paved the way for emergence of cancer Radiomics. However, effectiveness and accuracy of Signal Processing and Machine Learning solutions in this field heavily rely on availability of segmented tumor region, i.e., prior knowledge of where the tumor locates. Consequently, among the aforementioned four tasks, Segmentation is considered as the initial and the main critical task to further advance cancer Radiomics. The conventional clinical approach towards segmentation is manual annotation of the tumour region, however, it is extremely time consuming, depends on the personal expertises/opinion of the clinician, and is extensively sensitive to inter-observer variability. To address these critical issues, automatic (semi-automatic) segmentation methods are currently investigated (e.g. image-level tags or bounding boxes) to minimize manual input, increase consistency in labeling the tumor cancer region, and to obtain accurate and acceptable results in comparison to manually labeled data.

In the 2018 VIP-CUP, we propose a challenge for segmentation of Lung Cancer Tumor region based on a data set consisting of pre-treatment Computed Tomography (CT) scans of several (more than 400) patients. For the initial stage of the competition, a subset of the data along with the annotations will be provided as the training set together with a smaller subset for validation purposes. The evaluation will then be performed based on a test set provided closer to the submission deadline. For segmenting tumors, the competition teams can choose to utilize the conventional image processing techniques or deep learning methods however based on the available shallow datasets.


The Champion: $5,000

The 1st Runner-up: $2,500

The 2nd Runner-up: $1,500

​​Travel Support to Athens

Each finalist team invited to the ICIP 2018 will receive travel support by the IEEE SPS on a reimbursement basis. A team member is offered up to $1,200 for continental travel, or $1,700 for intercontinental travel. A maximum of 3 members per team will be eligible for travel support.

Eligibility Criteria

Each team must be composed of: (i) One faculty member (the Supervisor); (ii) At most one graduate student (the Tutor), and; (iii) At least 3 but no more than 10 undergraduates. At least three of the undergraduate team members must be either IEEE Signal Processing Society (SPS) members or SPS student members.

​​Important Dates

May 24, 2018Initial Dataset for training and validation will be released.
July 15, 2018Team registration on IEEE VIP-Cup.
August 14, 2018Test Data Will be Released.
August 26, 2018Deadline for Submission of VIP-Cup Results together with the Report.
August 26, 20182018 VIP-Cup Finalist Teams will be announced.
October 7, 2018VIP-CUP Final Competition at ICIP 2018​