Dr Rahele Kafieh

Welcome to my page

Here you can find my research and educational activities.


I am a guest researcher at Neurocure Clinical Research Center, Charite University, Berlin, Germany. I already work on deep learning for segmentation and classification of ocular data in Neurodegenerative diseases.

Im also an Assistant Professor at School of Advanced Technologies in Medicine, Isfahan University of Medical Sciences, Isfahan, Iran. My research is concentrated on biomedical image analysis. I am interested in problems in area of graph based image analysis, time-frequency methods, deep learning, image segmentation, restoration and others.

  • I received my BSc in Biomedical Engineering (Bio electrics) at Sahand University of Technology (2004) 
  • and completed my Msc and PhD in Biomedical Engineering (Bio electrics) at Isfahan University of Medical Sciences (2008 and 2014). 
  • I was also Post-doc at Faculty of Engineering and Natural Sciences, Sabanci University, Istanbul, Turkey (Mar.- Sep. 2015)

Ocular image processing

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Research activities


Automatic analysis of Ocular images

I'm a member of ocular image processing research group from 2010. Our team is concentrated on modelling, preprocessing, segmentaion, feature extraction and ultimately classification of images taken from eyes. The data is in varios forms, from 2D and 3D images to videos, taken from anterior to posterior regions of eye, using variety of imaging devices like optical coherence tomography (OCT), fundus, angiography and electroretinography signals.

Oct 01, 2010

Neurodegenerative diseases in OCT and MR data

We are eager to analyse MR and OCT features in diseases like Multiple Sclerosis (MS), parkinson, ... to find mutual features in both modalities and possibly help to early detection.

Jan 02, 2017

Automatic classification of Multiple Slerosis and Devic diseases by deep learning

Two similar diseases of MS and NMO have possiblity of being misdiagnosed and we try to propose a deep learning technique to distinguish them. Open positions for PhD students and researchers in avaiable in this area. Please send an email for me.

Feb 03, 2018



You can find my resume here: raheleKafiehCV2018Nov.pdf

Other links include:

Google scholar link



In this paper, we introduce a fast segmentation method based on a new variant of spectral graph theory named diffusion maps.

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Here, we review some of the important image segmentation methods for processing retinal OCT images. We may classify the OCT segmentation approaches into five distinct groups according to the image domain subjected to the segmentation algorithm.

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A texture-based algorithm is introduced in this paper for fully automatic segmentation of choroidal images obtained from an EDI system of Heidelberg 3D OCT Spectralis.

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In this research, the infrared video sequences from the cooling step of the pipeline welding procedure were collected in Chahar_Mahal_O_Bakhtiari/Iran gas Company. Choosing the best clustering algorithm by introducing proper coefficients, the proposed method could discriminate the occurred flaws, even better than destructive approaches.

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In this paper, we discuss about applications of different methods for decomposing a signal over elementary waveforms chosen in a family called a dictionary (atomic representations) in optical coherence tomography (OCT). The algorithm is evaluated in denoising of 144 randomly selected slices from twelve 3D OCTs taken by Topcon 3D OCT-1000 and Cirrus Zeiss Meditec. Improvement of contrast to noise ratio (CNR) (from 0.9 to 11.91 and from 3.09 to 88.9, respectively) is achieved.

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Useful links

Free avaiable datasets

This page is used for listing the avaiable medical dataset (with emphasis on ocular data) from our group or other research groups.

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Free OCT analysis softwares

This page is used for listing the free OCT analysis softwares.

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Deep learning resources

Useful websites for deep learning

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  • Charit√© - Campus Mitte (Berlin), Berlin, Germany