Hossein Rabbani, PhD, SMIEEE

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Here you can find my research/educational activities

About


About
I am currently a Professor at Isfahan University of Medical Sciences, in Biomedical Engineering Department also Medical Image & Signal Processing Research Center. Involved research topics include medical image analysis and modeling, statistical (multidimensional) signal processing, sparse transforms, and image/video restoration.

I received my Msc and PhD in Biomedical Engineering (Bioelectrics) from Amirkabir University of Technology (Tehran Polytechnic) which I was a Visiting Research Scholar in Queen's University for completion of my PhD. I also was a Postdoctoral Research Fellow in Duke University and Postdoctoral Research Scholar in the University of Iowa. Previously, I received a BSc (Hons) in Electrical Engineering (Communications) from Isfahan University of Technology.

You can download my CV.

NEWS


Missing Surface Estimation Based on Modified Tikhonov Regularization: Application for Destructed Dental Tissue

DOI: 10.1109/TIP.2018.2800289

IEEE Transactions on Image Processing, 27(5): 2433-2446, 2018.

Research


Field of Interests

Currently I am focusing on Statistical & Mathematical Modeling of Medical Signals and Systems. In this base, my field of interests consists of introducing efficient algorithms for biomedical signal analysis and processing including multidimensional data, time-frequency analysis tools including x-lets, denoising and signal/image recovery, and statistical signal processing.

Learn MoreDec 01, 2015

MISP research center

Medical Image and Signal Processing (MISP) Research Center is located at the heart of Isfahan University of Medical Sciences. The center was established in 2005 with close collaboration of faculty members from Isfahan University of Medical Sciences and Isfahan university of Technology. At MISP we work on different aspects of biomedical engineering, biomedical image and signal processing. We are dedicated to find new technical solutions for medical devices and fill the gap between the medical and engineering communities. Our missions are To create a place for researchers to work on fundamental, applied and interdisciplinary research projects. To communicate with government in order to contribute to society's health To highlight scientific influence of Isfahan University of Medical Sciences in national and international communities. More information are available at http://misprc.ir.

Learn MoreMar 14, 2016

Available Datasets

You can freely download/upload the datasets from: Isfahan MISP Datasets (biosigdata.com)

Learn MoreApr 27, 2018

Atomic Representation

A Summarized Table about Atomic Representation

Learn MoreApr 27, 2018

Image Restoration

State-of-the-art Method for Image Restoration

Learn MoreApr 27, 2018

Image Modeling

A Summarized Table about Image Modeling

Learn MoreApr 27, 2018

Optical Coherence Tomography Image Analysis

Check It Out Today!

Wiley EEEE Book Chapter doi.org/10.1002/047134608X.W8315

Course Materials


Spring 2018

Please visit misprc.ir/moodle

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2017

Please visit misprc.ir/moodle

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Before 2017

Please visit misprc.ir/moodle

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Fluid/Cyst Segmentation in Optical Coherence Tomography

Check It Out Today!

A. Rashno, D. D. Koozekanani, P. M. Drayna, B. Nazari, S. Sadri, H. Rabbani, K. K. Parhi, "Fully Automated Segmentation of Fluid/Cyst Regions in Optical Coherence Tomography Images With Diabetic Macular Edema Using Neutrosophic Sets and Graph Algorithms," IEEE Transactions on Biomedical Engineering, vol. 65, no. 5, pp. 989-1001, May 2018. A. Rashno, B. Nazari, D. D. Koozekanani, P. M. Drayna, S. Sadri, H. Rabbani, K. K. Parhi, "Fully-automated segmentation of fluid regions in exudative age-related macular degeneration subjects: Kernel graph cut in neutrosophic domain," PLoS ONE 12(10): e0186949. M. Esmaeili, A. Mehri, H. Rabbani, F. Hajizadeh, “Three-dimensional segmentation of retinal cysts from spectral-domain optical coherence tomography images by the use of three-dimensional curvelet based k-SVD ,” Journal of Medical Signals & Sensors, vol. 6, no. 3, pp. 166–171, 2016.

Available Datasets


Dataset for Fluorescein Angiography (Video & Late Image) in DME eyes

The datasets (24 768*768*x FA videos and late FA images in DME eyes) and manual and automated markings used in the following paper can be downloaded from HERE.

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OCT data & Color Fundus Images of Left & Right Eyes of 50 healthy persons

This dataset contains OCT data (in mat format) and color fundus data (in jpg format) of left & right eyes of 50 healthy persons.

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Bone Marrow Microscopic Data (plasma cell lineage images)

This folder contains bone marrow microscopic images. These images are categorized into two groups: Normal Plasma Cells and Myeloma Cells.

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Fundus Fluorescein Angiogram Photographs of Diabetic Patients

We have collected retinal image of 70 patients of different diabetic retinopathy stages including 30 normal data and 40 abnormal data in different stages.

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Dataset of Leishmania Parasite in Microscopic Images

45 24-bit 3264*2448 microscopic images taken from bone marrow samples including leshman bodies.

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CT & MR Volumes Used for Watermarking of DICOM Images

This dataset contains 260 CT and 202 MR images in DICOM format.

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Fundus Fluorescein Angiogram Photographs & Colour Fundus Images of Diabetic Patients

Publicly available database of both fundus fluorescein fngiogram photographs and corresponding color fundus images of 30 healthy persons and 30 patients with diabetic retinopathy.

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Database of corneal OCT taken from Heidelberg OCT imaging system (3D .mat data of 15 subjects)

A set of 2D .mat corneal OCT images of 15 subjects. For example subject#1 includes 41 240×748 B-scans taken from Heidelberg OCT imaging device.

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Colour Fundus Images of Healthy Persons & Patients with Diabetic Retinopathy

This folder includes 25 colour fundus images of healthy persons and 35 colour fundus images of patients with diabetic retinopathy used for automatic curvelet-based detection of Foveal Avascular Zone (FAZ).

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Database of 22 retinal images for the purpose of vessel-based registration of Fundus and OCT projection images of retina

A set of eye images consisting of 22 pairs of images (17 macular and 5 prepapillary), from random patients, each pair acquired from eyes with a variety of retinal diseases. Each image pair includes a colour fundus image and one OCT image acquired with Topcon 3D OCT-1000 instrument. OCT images contain images of 650 different slices with a size of 650 × 512 × 128 voxels and a voxel resolution of 3.125 µm × 3.125 µm × 7 µm.

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Red blood cells

A self-provided dataset contains 148 microscopic images of blood smears.

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Kidney microscopic images (Glomeruli)

A dataset for Glomeruli detection was collected with the contribution of MISP Research Center and Department of Pathology at IUMS

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Dataset for OCT Classification (50 Normal, 48 AMD & 50 DME)

This dataset is acquired at Noor Eye Hospital in Tehran and is consisting of 50 normal, 48 dry AMD, and 50 DME OCTs.

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ONH-based OCT of 7 healthy and 7 glaucoma data captured by Heidelberg Spectralis

7 healthy and 7 glaucoma data captured by Heidelberg Spectralis used to demonstrate the efficacy of a new imaging biomarker namely Volumetric Cup-to-Disc Ratio (VCDR) for diagnosis of ocular diseases such as Glaucoma.

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