ITEC @ Lange Nacht der Forschung 2018

On April 13, 2018 the ‘Lange Nacht der Forschung 2018‘ (long research night) took place again in Austria and the medical multimedia research group of ITEC did also participate in this exciting event that communicates research works to the public. Our booth at Klagenfurt University showed ‘How neural networks can help surgeons to improve surgical quality‘ and it was a great success: several thousands of people came to see our research efforts and they were stunned by our interesting demos and hands-on experiences: real-time instruments detection, real-time smoke detection (with dry ice), and several laparoscopic operation simulator boxes where visitors could test their surgical skills (we also had an original KARL STORZ Endoscope with corresponding laparoscopic instruments).

First six photos by photo riccio.

Best Demo Award at MMM 2018

We are very happy that we received the Best Demo Award at the 24th International Conference on Multimedia Modeling (MMM 2018) for our demo on “Video Browsing on a Circular Timeline“.

Medical Image and Video Analysis Using Deep Learning – Deadline Extended!

The submission deadline for our Special Track on Medical Image and Video Analysis using Deep Learning at the 31st IEEE CBMS International Symposium on Computer-Based Medical Systems (CBMS 2018), to be held in Karlstad, Sweden from June 18-21, 2018, has been extended until March 5, 2018! Find more information here.

Results of the VBS 2018

The 7th Video Browser Showdown (2018) at the 24th International Conference on Multimedia Modeling (MMM 2018), held from February 5-7, 2018 in Bangkok, Thailand was a great and entertaining event! We had 9 very competitive teams from 8 different countries that challenged each other for several hours and performed 20 tasks in the public session (as well as 8 training tasks in the private session on February 4th). The novices in the Novice Run were highly active and performed very well! Moreover, we had hard-working judges that performed live-judgement for more than 1500 submissions (that couldn’t be found in the TRECVID groundtruth). Congratulations to the SIRET team from Czech Republic that won the VBS 2018! We are also very happy that Klagenfurt University (ITEC-1 and ITEC-2) scored very well with place 2 and 3.¬†Here are all the details and results of this year’s VBS.


Medical Image and Video Analysis using Deep Learning – Deadline Extended!

We are happy to announce that our Special Track on Medical Image and Video Analysis using Deep Learning at the 31st IEEE CBMS International Symposium on Computer-Based Medical Systems, to be held in Karlstad, Sweden from June 18-21, 2018, has been accepted!

Topics of interest include (but are not limited to):

  • Novel approaches for medical image/exam classification, object/lesion classification, organ/region/landmark localization, object/lesion detection, organ/substructure segmentation, lesion segmentation, and medical image registration using deep learning;
  • Content-Based Image Retrieval (CBIR) of medical images using deep learning;
  • Medical image content understanding using deep learning;
  • Medical image generation and enhancement methods using deep learning;
  • Multimodal (image/text) analysis using deep learning;
  • Organ-specific, modality-specific, and disease-specific image analysis using deep learning;
  • Applications of deep learning for digital pathology and microscopy.

Please find the Call-for-Papers here. We are looking forward to your submissions!

  • Abstract submission deadline: February 5, 2018
  • Full paper submission deadline: February 19, 2018
  • Notification of acceptance: April 25, 2018
  • Final paper submission deadline: May 7, 2018

Medical Multimedia Information Systems

The slides of our tutorial on Medical Multimedia Information Systems, held together with Bernd M√ľnzer, Paal Halvorsen, and Michael Riegler at the 25th ACM International Conference on Multimedia 2017 (ACMMM17) can be found on slideshare:

SurgicalActions160 Dataset

We are happy to announce that the SurgicalActions160 dataset is available for download here. The dataset consists of short video clips representing 16 typical actions in gynecologic laparoscopy, which have been compiled from different surgeries. For each action class there are exactly 10 example clips.

More information about the dataset can be found in our recent MTAP paper:

Best Paper at CARE 2017 (MICCAI 2017)

We are very happy that our paper on “Image-Based Smoke Detection in Laparoscopic Videos” has been awarded as Best Paper at the 4th International¬†¬†Workshop on Computer Assisted and Robotic Endoscopy (CARE 2017) at the 20th International Conference on Medical Image Computing and Computer Assisted Intervention 2017 (MICCAI 2017) conference in Quebec, Canada.

A preprint of the paper can be found here.

Call-for-Papers: MMM 2018 and VBS 2018 – Extended Deadline!

The International Conference on Multimedia Modeling 2018 (MMM 2018), including the 7th Video Browser Showdown competition (VBS 2018), will be held in Bangkok, Thailand from February 5-7, 2018.

Please submit your regular papers and special-session papers until:
September 15, 2017 (extended).

Demo papers and papers for the VBS need to be submitted until:
October 15, 2017 (extended)

More information can be found here.

New Journal Papers on Medical Multimedia

Our research group has published two new journal papers in the Multimedia Tools and Applications (MTAP) Journal by Springer.

The first one is a survey paper on Content-based processing and analysis of endoscopic images and videos: A survey¬†(by Bernd M√ľnzer, Klaus Schoeffmann, and Laszlo B√∂sz√∂rmenyi) and covers a broad overview of proposed methods to analyze videos and images in the domain of medical endoscopy. The preprint is available¬†here.

The second one covers Learning laparoscopic video shot classification for gynecological surgery (by Stefan Petscharnig and Klaus Schoeffmann) and evaluates the performance of Convolutional Neural Networks (CNNs) for video shot classification in medical laparoscopy, more specifically in the field of gynecology. The preprint is  already here.