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--- research_group:start [2020/05/06 18:47]
pkleczek [Computer-aided histopathology]
+++ research_group:start [2020/05/06 20:57]
mpiekarski [Anomaly detection with the use of pre-trained CNN architectures]
@@ Line 1: / Line 1: @@
 ====== MVG Research Group ======
-FIXME
+{{page>research_group:includes:intro&nofooter&noheader&noindent}}
 ===== Research area =====
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 FIXME
-====  Computer-aided histopathology ====
+====  Computer-aided dermatopathology ====
 **Research goal:**\\
@@ Line 16: / Line 16: @@
   * tissue segmentation
   * epidermis segmentation
+  * nests of melanocytes segmentation
   * epidermal morphometry measurement
+Team members involved:
+  * J. Jaworek-Korjakowska
+  * P. Kłeczek
+  * D. Kucharski
 ++++ Research activity |
+Publications:
   * **Dariusz Kucharski**, **Pawel Kleczek**, **Joanna Jaworek-Korjakowska**, Grzegorz Dyduch, Marek Gorgon. //Semi-Supervised Nests of Melanocytes Segmentation Method Using Convolutional Autoencoders//. Sensors, 2020, vol. 20, issue 6, 1546, doi: [[https://doi.org/10.3390/s20061546|10.3390/s20061546]]  ([[https://www.mdpi.com/1424-8220/20/6/1546/htm|HTML]])  \\ [size=80%][IF5 (2018) = 2.737, Top10][/size]
   * **Pawel Kleczek**, **Joanna Jaworek-Korjakowska**, Marek Gorgon. //A novel method for tissue segmentation in high-resolution H&E-stained histopathological whole-slide images//. Computerized Medical Imaging and Graphics, 2020, vol. 79, 2022, Art. ID 101686, doi: [[https://doi.org/10.1016/j.compmedimag.2019.101686|10.1016/j.compmedimag.2019.101686]]  ([[https://www.sciencedirect.com/science/article/pii/S0895611119301016|HTML]])  \\ [size=80%][IF5 (2018) = 2.737, Top10][/size]
@@ Line 25: / Line 34: @@
   * **Paweł Kłeczek**, Grzegorz Dyduch, **Joanna Jaworek-Korjakowska**, Ryszard Tadeusiewicz. //Automated epidermis segmentation in histopathological images of human skin stained with hematoxylin and eosin//. Proc. SPIE 10140, Medical Imaging 2017: Digital Pathology, 101400M (2017). doi: [[https://doi.org/10.1117/12.2249018|10.1117/12.2249018]]. ([[http://proceedings.spiedigitallibrary.org/proceeding.aspx?articleid=2608559|Abstract]], [[https://drive.google.com/open?id=0B1Rp-jhc52-PQldnMjZNM01tUVk|Poster PDF]])
   * **Paweł Kłeczek**, Sylwia Mól, **Joanna Jaworek-Korjakowska**. //The Accuracy of H&E Stain Unmixing Techniques When Estimating Relative Stain Concentrations//. PCBBE 2017: Advances in Intelligent Systems and Computing, Springer (2017), doi: [[http://dx.doi.org/10.1007/978-3-319-66905-2_7|10.1007/978-3-319-66905-2_7]], pp. 87--97 ([[https://link.springer.com/chapter/10.1007/978-3-319-66905-2_7|Abstract]])
+Conferences:
+  * [[https://spie.org/conferences-and-exhibitions/past-conferences-and-exhibitions/medical-imaging-2018?SSO=1|SPIE Medical Imaging 2018]] (Houston, TX, USA) \\ **Paweł Kłeczek**: //Segmentation of black ink and melanin in skin histopathological images//((All authors: **P. Kłeczek**, M. Lech, G. Dyduch, **J. Jaworek-Korjakowska**, R. Tadeusiewicz.)) [size=80%](poster)[/size]
+  * [[http://www.pcbbe.agh.edu.pl/|20-th Polish Conference on Biocybernetics and Biomedical Engineering]] (Kraków, Polska) \\ **Paweł Kłeczek**: //The accuracy of H&E stain unmixing techniques when estimating relative stain concentrations//((All authors: **P. Kłeczek**, S. Mól, **J. Jaworek-Korjakowska**)) [size=80%](poster)[/size]
+  * [[https://spie.org/conferences-and-exhibitions/past-conferences-and-exhibitions/medical-imaging-2017|SPIE Medical Imaging 2017]] (Orlando, FL, USA) \\ **Paweł Kłeczek**: //Automated epidermis segmentation in histopathological images of human skin stained with hematoxylin and eosin//((All authors: **P. Kłeczek**, G. Dyduch, **J. Jaworek-Korjakowska**, R.Tadeusiewicz)) [size=80%](poster)[/size]
 ++++
 ==== Anomaly detection with the use of pre-trained CNN architectures ====
-FIXME
+**Research goal:**\\
+To detect anomalies in multivariate diagnostic signals of the synchrotron control system by pre-trained CNN architectures.
+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. Currently, just slow-changing anomalies are detected only by experienced operators but even those faults are recognized far too late. 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.
+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 (@asia: muszę dopracować ) ====
 FIXME
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-<nspages -subns -textNS="Kategorie" -textPages="Strony" -title -hideNoPages -hideNoSubns -exclude>
+<nspages -subns -textNS="Kategorie" -textPages="Strony" -title -hideNoPages -hideNoSubns -exclude -r -pregNSOff="/includes/" -pregPagesOff="/includes.*/" >

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