The Tuberculosis and Caption ImageCLEF research tasks are now available online: https://www.crowdai.org/challenges.
More information on the tasks and schedule are available here.
The journal paper “Rotation-Covariant Tissue Analysis for Interstitial Lung Diseases Using Learned Steerable Filters: Performance Evaluation and Relevance for Diagnostic Aid” by Ranveer Joyseeree, Henning Müller and Adrien Depeursinge was accepted for publication at Computerized Medical Imaging and Graphics (CMIG).
More information on the website: http://fst.ch/fr/
The paper “OCT-NET: A convolutional network for automatic classification of normal and diabetic macular edema using SD-OCT volumes” by Oscar Julian Perdomo, Sebastian Otálora, Fabio González, fabrice Meriaudeau and Henning Müller was accepted at the 2018 IEEE International Symposium on Biomedical Imaging: ISBI 2018
A new video was published on youtube showing our current tests to control a 3D printed hand in real time with surface electromyography.
New milestone for ContextVision/HES-SO: Presents demo of a new search tool for digital pathology.
Henning Müller is giving a 90 min presentation today on ” Visual medical decision support and medical information retrieval: new ideas for business models” at Digital Product School (https://www.digitalproductschool.io)
Adrien Depeursinge presented his work on “Leveraging 3D texture information in PET and CT images for precision medicine with the QuantImage platform” at the predictive radiology workshop on November 13th, 2017 in the Lausanne University Hospital CHUV.
Link to the slides: https://drive.switch.ch/index.php/s/4nC3sGKPNgWcxnN
Roger Schaer presented his work on “
Sebastian Otalora introduced his work on “Deep Learning in small medical datasets: An active learning approach” at a spotlight session.
The journal article “Comparison of six electromyography acquisition setups on hand movement classification tasks” has been accepted in Plos One and is now available here: http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0186132
The journal article ‘Large-scale retrieval for medical image analytics: A comprehensive review’ by Zhongyu Li, Xiaofan Zhang,Henning Müller and Shaoting Zhang has been published in Medical Image Analysis.
The journal article “Retrieval From and Understanding of Large-Scale Multi-modal Medical Datasets: A Review” has been accepted in IEEE Transactions on Multimedia and is now available in IEEEXplore:
The manuscript ‘Retrieval from and Understanding of Large–Scale Multi–modal Medical Datasets: A Review’ by Devrim Unay et al. has been accepted for publication as a regular paper at the IEEE Transactions on Multimedia journal.
The CLEF 2017 Working Notes have been published in CEUR-WS as volume 1866: http://ceur-ws.org/Vol-1866/
The CLEF 2017 conference is the eighteenth edition of the popular CLEF campaign and workshop series which has run since 2000 contributing to the systematic evaluation of multilingual and multimodal information access systems, primarily through experimentation on shared tasks. In 2010 CLEF was launched in a new format, as a conference with research presentations, panels, poster and demo sessions and laboratory evaluation workshops. These are proposed and operated by groups of organizers volunteering their time and effort to define, promote, administrate and run an evaluation activity. CLEF 2017 was hosted by the ADAPT Centre , Dublin City University and Trinity College Dublin from the 11th to 14th September 2017. This year’s conference was also co-located with MediaEval and the program included joint sessions between both MediaEval and CLEF to allow for cross fertilisation.
The goal of the MCV workshop is to explore the use of “big data” algorithms for harvesting, organizing and learning from large-scale medical imaging data sets and for general-purpose automatic understanding of medical images.
The BAMBI workshop aims to highlight the potential of using Bayesian or random field graphical models for advancing research in biomedical image analysis.
The NVIDIA GPU grant program awarded a Titan Xp to the MEGANE PRO project.
Hand amputations are highly impairing and can dramatically affect the capabilities people. Man-machine interfaces that can control hand prostheses have been developed, but natural control methods are still only rarely applied in real life. The requested GPU will allow us to develop this research field that has high scientific and social impact. The project includes the development of highly specific data classification and fusion algorithms based on convolutional and recurrent neural networks. The algorithms will allow to control a 3D printed prosthetic hand and/or a robotic hand simulator based on virtual reality in real time.
The paper “Classification of SD-OCT images using Deep learning approach” has been accepted for oral presentation at the IEEE International Conference on Signal and Image Processing Applications (IEEE ICSIPA) 2017.
The conference will take place from September 12-14, 2017 in Kuching, Malaysia.