Novel Imaging Methods for Diagnosis and Screening of Ophthalmic Diseases Call for Papers

CALL FOR PAPERS - ICIAR 2020 Special Session

Novel Imaging Methods for Diagnosis and Screening of Ophthalmic Diseases

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

- 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

Submission Procedure

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 

Important Dates

 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

Special Session Chairs

A.M. Mendonša, PhD
  Faculty of Engineering & INESC Technology and Science
  University of Porto

K.A. Vermeer, PhD
  Rotterdam Ophthalmic Institute, Rotterdam Eye Hospital