Dear Colleagues, 

The second workshop on machine learning approaches in high resolution microscopy will be held in conjunction with the IEEE BIBM 2019 conference in San Diego, CA, USA. Please find the call for papers below.  The workshop web site, topics, and dates are available here: 

www.mlhrm.net/2019

Please do not hesitate to reach out for any questions. 
Best, 

Filiz Bunyak, Ilker Ersoy, Tommi White

University of Missouri Columbia

=====================================================================
                        CALL FOR PAPERS
        SECOND WORKSHOP ON MACHINE LEARNING APPROACHES
             IN HIGH RESOLUTION MICROSCOPY IMAGING
                          MLHRM 2019
                      www.mlhrm.net/2019

                      in conjunction with

2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM19)
           November 18-21, 2019, San Diego, CA, USA
                 http://ieeebibm.org/BIBM2019/

Description:
With the advent of higher resolution imaging modalities, such as electron
microscopy (Cryo-EM, FIB-SEM) and fluorescence superresolution microscopy
(SRM), scientists are able to discern subcellular structures at the molecular
level leading to discoveries in basic and translational sciences as well as
applications in drug discovery and precision medicine. Visualizing cellular,
sub-cellular, and protein structures have been recently recognized with
Nobel Prizes in Chemistry, for super-resolution fluorescence microscopy in
2014 and for cryo-electron microscopy in 2017. SRM imaging achieves nanometer
resolution while cryo-EM allows imaging of structures in their native, frozen,
hydrated state by resolving structural details of 1.5 Angstrom. These imaging
modalities as well as many others rely on performant computational techniques
to reconstruct high resolution images in 2D and 3D for visualization and
further quantitative analysis. Advances in machine learning, particularly in
deep learning, has a great potential to contribute to high resolution
reconstruction process, particularly by improving particle detection and
classification steps of reconstruction.

This second workshop aims to bring the researchers from computational and
imaging fields together to have a wider focus on the computational approaches
that learn parameters from image data while maintaining an emphasis on
the leading edge machine learning methods such as deep learning for all
computational tasks: segmentation, classification, construction, and analysis
in high resolution imaging modalities (cryo-electron microscopy, FIB-SEM
tomography and fluorescence superresolution microscopy).

Topics:
Original contributions in applications of deep learning and other machine
learning methods in high resolution microscopy including but not limited
to noise reduction, detection, segmentation, classification, and
reconstruction of 2D and 3D models, as well as new approaches in 3D
reconstruction of single molecules are welcome. Contributions regarding
other related modalities and automated analysis methods such as single
molecule tracking, multiphoton imaging, and combining EM with STORM/PALM
will also be considered for inclusion in the workshop program.

- Noise reduction in EM modalities and SRM
- Signal detection and image reconstruction in SRM
- Image segmentation in EM modalities
- Image classification in EM modalities and SRM
- 3D reconstruction methods and pipelines in cryo-EM
- Characterization of single molecule structure using machine learning
- Applications of high resolution microscopy in precision medicine
- Applications in single molecule tracking, multiphoton imaging

Paper Submission:
Please submit a full-length original and unpublished research contribution
(up to 6 pages in IEEE 2-column format) through the online submission system
(you can download the format instructions at
http://www.ieee.org/conferences_events/conferences/publishing/templates.html).

Electronic submissions in PDF are required. Selected participants will be
asked to submit their revised papers in a format to be specified at the time
of acceptance. All papers will be published in conference proceedings and
indexed by IEEE Xplore. Workshop organizers may select a small number of
workshop papers to be extended and published in a journal.

Online Submission: https://wi-lab.com/cyberchair/2019/bibm19/index.php

Important Dates:
Electronic submission of full workshop papers: Sep 20, 2019
Notification of paper acceptance to authors: Oct 15, 2019
Camera-ready version of accepted papers: Nov 1, 2019
Workshop and Conference: Nov 18-21, 2019

Workshop Chairs:
Dr. Filiz Bunyak, Department of Electrical Engineering and Computer Science, University of Missouri, USA.
Dr. Ilker Ersoy, Informatics Institute, University of Missouri, USA.
Dr. Tommi White, Electron Microscopy Core, Department of Biochemistry, University of Missouri, USA.

Workshop Program Committee Members:
Dr. Joseph Brzostowski, NIAID Twinbrook Imaging Facility, National Institutes of Health, USA.
Dr. Yuejie Chi, Department of Electrical and Computer Engineering, Carnegie Mellon University, USA.
Dr. Stefan Jaeger, National Library of Medicine, National Institutes of Health, USA.
Dr. Rengarajan Pelapur, Thermo Fisher Scientific, USA.
Dr. Surya Prasath, Department of Biomedical Informatics, Cincinnati Children's Hospital Medical Center, USA.
Dr. Satoshi Sawai, Research Center for Complex Systems Biology, University of Tokyo, Japan.
Dr. Mingzhai Sun, Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China.
Dr. Devrim Unay, Department of Biomedical Engineering, Izmir University of Economics, Turkey.

########################################################################

To unsubscribe from the CCPEM list, click the following link:
https://www.jiscmail.ac.uk/cgi-bin/webadmin?SUBED1=CCPEM&A=1