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research_group:start [2020/05/06 18:48]
pkleczek [Computer-aided histopathology]
research_group:start [2021/11/04 18:01]
abrodzicki
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 ====== MVG Research Group ====== ====== MVG Research Group ======
  
-FIXME+{{page>​research_group:​includes:​intro&​nofooter&​noheader&​noindent}}
  
 ===== Research area ===== ===== Research area =====
  
 ==== Deep neural networks in early detection of melanomas ==== ==== Deep neural networks in early detection of melanomas ====
-FIXME 
  
-====  Computer-aided ​histopathology ​====+====  Computer-aided ​dermatopathology ​====
  
 **Research goal:**\\ **Research goal:**\\
Line 16: Line 15:
   * tissue segmentation   * tissue segmentation
   * epidermis segmentation   * epidermis segmentation
 +  * nests of melanocytes segmentation
   * epidermal morphometry measurement   * epidermal morphometry measurement
 +
 +Team members involved:
 +  * J. Jaworek-Korjakowska
 +  * P. Kłeczek
 +  * D. Kucharski
  
 ++++ Research activity | ++++ Research activity |
Line 38: Line 43:
 ++++ ++++
 ==== Anomaly detection with the use of pre-trained CNN architectures ==== ==== Anomaly detection with the use of pre-trained CNN architectures ====
-FIXME 
  
-==== Detection and analysis of patterns (@asiamuszę dopracować ) ==== +**Research goal:**\\ 
-FIXME+To detect anomalies in multivariate diagnostic signals of the synchrotron control system by pre-trained CNN architectures.
  
-==== Cell detection - Andrzej... ====+[[https://​synchrotron.uj.edu.pl|SOLARIS]] National Synchrotron Radiation Centre is a research facility that provides high quality synchrotron light. To control such a complex system it is necessary to monitor signals from various devices and subsystems. Anomaly detection prevents from financial loss, unplanned downtimes and in extreme cases cause damage. As artificial intelligence techniques including machine learning and deep neural networks have become state-of-the-art solutions for anomaly detection tasks which are one of the most challenging in data analysis, our team conducts research on the use of them for anomaly detection in multivariate diagnostic signals.
  
-FIXME+The research topics include: 
 +  * data mining and preparation 
 +  * data preprocessing 
 +  * CNN architectures building
  
 +Team members involved:
 +  * M. Piekarski
 +  * J. Jaworek-Korjakowska
 +==== Detection and analysis of patterns ====
  
 +==== Cell detection ====
 +
 +To improve speed and quality of testing new drugs against Clostridium difficile infection, we developed an algorithm for automatic bacteria cytotoxicity classification. It was based on two kinds of fluorescence images - DAPI and GFP. We experimented with many different methods from classical image processing and machine learning algorithms to convolutional neural networks. This research was was conducted in cooperation with Stanford University.
 +
 +The research topics include:
 +  * fluorescence images
 +  * image processing
 +  * sharing information from different images
 +  * convolutional neural networks
 +
 +Team members involved:
 +  * J. Jaworek-Korjakowska
 +  * A. Brodzicki
 +
 +==== Bacteria response clustering ====
 +
 +Newly opened project, in cooperation with Stanford University. The main idea is to analyse bacteria reaction in response to different serums.
 +
 +The research topics include:
 +  * data clustering
 +  * bacteria response analysis
 +
 +Team members involved:
 +  * J. Jaworek-Korjakowska
 +  * A. Brodzicki
 +
 +==== Reconstructing images'​ missing areas with generative models ====
 +
 +The research topics include:
 +  * reconstruction
 +  * generative learning
 +  * GANs
 +  * autoencoders
 +
 +Team members involved:
 +  * J. Jaworek-Korjakowska
 +  * D. Kucharski
 +
 +==== Vehicle interior image segmentation ====
 +
 +The research topics include:
 +  * dataset preparation
 +  * image classification
 +  * image segmentation
  
 +Team members involved:
 +  * J. Jaworek-Korjakowska
 +  * A. Kostuch
  
 ---- ----
  
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research_group/start.txt · Last modified: 2021/11/04 18:01 by abrodzicki