Novel Imaging Methods for Diagnosis and Screening of Ophthalmic Diseases Call for Papers
CALL FOR PAPERS - ICIAR 2020 Special Session
https://www.aimiconf.org/iciar20/specialsessions.php
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Novel Imaging Methods for Diagnosis and Screening of Ophthalmic Diseases
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Fundus photography, fluorescence angiography, fundus autofluorescence and
optical coherence tomography (OCT) are some of the technologies that are
routinely used in clinical practice. In addition, several newer modalities are
being developed and evaluated, such as OCT-angiography, polarization- sensitive
OCT, multispectral imaging, oximetry and Raman spectroscopy.
The resulting 2D, 3D or 4D images provide new information on the morphology and
pathology of the cornea, lens, choroid and retina. Ophthalmologists cannot
manually review these datasets, because of a lack of time, but also because it
is largely unknown where the clinically relevant information is hidden in these
datasets. Image analysis and recognition can help to transform these large
datasets to clinically meaningful information. On the image level, this includes
the extraction of relevant features, transformation of image data and definition
of quantitative image-based biomarkers. On the level of large datasets,
technology may aid to identify biomarkers that are related to a disease or to
describe previously unknown effects of ophthalmic diseases.
Several of the mature imaging modalities are available in affordable, easy-to-
operate and robust imaging systems, making them suited for screening of common
ophthalmic diseases such as diabetic retinopathy, glaucoma and age-related
macular degeneration. Image analysis may further automate the process of
interpreting the acquired imaging by using conventional feature-based analysis
or, in the case of large data sets, modern deep-learning approaches.
This session focuses on image analysis methods and systems for detection and
screening of ophthalmic diseases.
Topics that are relevant to this special session include (but are not limited
to):
- Image processing to improve ophthalmic images;
- Registration of retinal images for mosaicking or longitudinal analysis;
- Image analysis for the extraction of qualitative or quantitative image-based
biomarkers in ophthalmology;
- Segmentation of anatomical landmarks or lesions;
- Deep-learning approaches, including CNN and other architectures, for the
diagnosis of ophthalmic diseases;
- Advanced machine learning architectures for screening of ophthalmic diseases;
- Modelling and synthesis of ophthalmic images;
- Embedding ophthalmic image-based CAD systems in a clinical workflow
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Submission Procedure
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Authors are invited to submit full papers showing original research
contributions. The conference proceedings will be published in the Springer
Lecture Notes in Computer Science series (Springer LNCS). Prospective authors
should submit an electronic copy of their complete manuscript through the ICIAR
2020 submission system by March 6, 2020, selecting the special session topic in
their submission. All submitted papers will be reviewed by at least two
independent reviewers. For more information please go to
https://www.aimiconf.org/iciar20.
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Important Dates
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Paper submission deadline March 6, 2020
Author notification March 27, 2020
Camera-ready version April 3, 2020
Paper registration April 10, 2020
Conference June 24-26, 2020
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Special Session Chairs
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A.M. Mendonça, PhD
Faculty of Engineering & INESC Technology and Science
University of Porto
amendon@fe.up.pt
https://sigarra.up.pt/feup/en/func_geral.formview?p_codigo=208752
K.A. Vermeer, PhD
Rotterdam Ophthalmic Institute, Rotterdam Eye Hospital
k.vermeer@eyehospital.nl
http://www.roi.eyehospital.nl/person/1/koen-vermeer-phd
http://www.linkedin.com/in/kavermeer/