Microscopic Image Analysis

Research Center

Preprocessing

Microscopic images of biological organs include vast

majority of variations based on the application, like cell

and tissue processing. Different artifacts arisen from

these diversities would be variations in color, illumina-

tion, movement, capturing system, etc. Some prepro-

cessing algorithms might be essential based on applica-

tion (image/video analysis), such as, denoising, deblur-

ring, registration, mosaicing, glim elimination, illumination

uniformity, etc.

Segmentation

Generally, microscopic image segmentation faces many

challenges and this concern will drastically increase

when the data are prepared without any standardiza-

tion. Cells usually follow a circular/elliptical pattern in

the most application and this might be a key-point in

developing algorithms. Microscopic images of tissue sec-

tions might defy more challenges and more powerful

methods must be utilized. Video processing of biological

cells might have the most challenges in this field due to

the artifacts mention in the preprocessing Section.

School of Advanced

Technologies in Medicine,

Isfahan University of

Medical Sciences

Microscopic Image Analysis Research Center (MIAC)

This center is established on January 13th, 2013 with the

aim to aid the doctors for the more accurate diagnosis

of diseases related to the field of pathology

(microscopic diagnostics) by developing systems which

are based on image processing techniques. This research

core has provided conditions for the development of

qualitative and quantitative research in the field of mi-

croscopy in the faculty of Advanced Medical Technology

(AMT). Students and researchers can choose their disser-

tation and research in line with related medical applica-

tions. Also, regarding the MIAC’s purposes, regular

meetings are held in the faculty to provide an effective

environment for discussion and exchange between pro-

fessors and students to advance the researches.

MIAC Goals:

Design and implementation of image processing

algorithms on microscopic images for the more accu-

rate and faster diagnosis of diseases

Development and improvement of existing methods

in the analysis of microscopic images for the diag-

nosis of leukemia (blood cancer), parasites, Pap

smear’s cancers and so on.

Producing microscopic image processing software

Holding congress and workshop related to the MI-

AC – (e.g., Workshop on Introduction to Graphical

User Interface (GUI) and commercialization of med-

ical software in MATLAB programming environment

in the Faculty of AMT on June, 2013)

http://amt.mui.ac.ir/en

http://misp.mui.ac.ir/

Selected journal papers and conference proceedings published by presenters:

Momenzadeh M, Vard A, Talebi A, Dehnavi AM, Rabbani H. Computer-aided diagnosis software for vulvovaginal candidiasis detec-tion from Pap smear images. Microsc Res Tech. pp:1–9, 2017. https://doi.org/10.1002/jemt.22951

MOMENZADEH, M., SEHHATI, M., MEHRI DEHNAVI, A., TALEBI, A. and RABBANI, H., Automatic diagnosis of vulvovaginal candidiasis from Pap smear images. Journal of Microscopy, 267: 299–308, 2017. doi:10.1111/jmi.12566

Soltanzadeh, R. , Rabbani, H. , Dehnavi AM, CIRCLET BASED FRAME-WORK FOR OPTIC DISK DETECTION , in Proc. IEEE ICIP 2017.

Soltanzadeh, R. , Rabbani, H. , " Classification of three types of red blood cells in peripheral blood smear based on morphology”, Signal Pro-cessing (ICSP), 2010 IEEE 10th International Conference on, pp:707 - 710 , 2010.

Soltanzadeh, R. , Rabbani, H., Talebi, A., “Extraction of Nucleolus Candidate Zone in White Blood Cells of Peripheral Blood Smear Images Using Curvelet Transform”. Comp. Math. Methods in Medicine, 2012.

Sheikhhosseini M1, Rabbani H, Zekri M, Talebi A. “Automatic diagno-sis of malaria based on complete circle-ellipse fitting search algorithm” J Microsc., 252(3):189-203, 2013.

Farahi, A., Talebi, A., Rabbani, H.,“Automated border extraction of Leishman bodies in bone marrow samples from patients with visceral leishmaniasis”, Journal of Isfahan Medical School, 32(286), 2014.

Sarrafzadeh, O., Rabbani, H.,Talebi, A., Yousefi-Banaem, H., “The best features selection for leukocytes classification in blood smear micro-scopic images” Proceedings of SPIE 2014, California, USA, 2014.

Sheikhhosseini, M., Rabbani, H., Zekri, M., Talebi A., “Automatic detection of malaria from blood smear microscopic images”, 1st National Conference on Microscopic Studies, Histomorphometry and Stereology Research Center, Shiraz University of Medical Sciences, Shiraz, Iran, 2014.

Farahi, A.,Talebi, A.,Rabbani, H.,Sarrafzadeh, O., “Automatic detec-tion of Leishman bodies in bone marrow samples of patients with visceral leishmaniasis using active contour”, 1st National Conference on Micro-scopic Studies, Histomorphometry and Stereology Research Center, Shiraz University of Medical Sciences, Shiraz, Iran, 2014.

Sarrafzadeh, O., Talebi, A., MehriDehnavi, A., Rabbani, A., “Automatic detection of acute myeloid leukemia from microscopic images of blood smear and bone marrow”, 1st National Conference on Microscop-ic Studies, Histomorphometry and Stereology Research Center, Shiraz University of Medical Sciences, Shiraz, Iran, 2014.

Moradia Amin, M., Kermani., S., Talebi, A., Sarrafzadeh, O., “Automatic Recognition of Acute Lymphoblastic Leukemia Cells in Micro-scopic Images”, 1st National Conference on Microscopic Studies, Histomor-phometry and Stereology Research Center, Shiraz University of Medical Sciences, Shiraz, Iran, 2014.

Moradia Amin, GhelichOghli, M., “A Novel Method for Leukemia Segmentation by Means of Superellipse Fitting”, 1st National Conference on Microscopic Studies, Histomorphometry and Stereology Research Center, Shiraz University of Medical Sciences, Shiraz, Iran, 2014.

Momenzadeh, M., Talebi, A., MehriDehnavi, A., Eshaghi, A., “Virtual microscopy and application of using digital blood smear”,1st National Conference on Microscopic Studies, Histomorphometry and Stereology Research Center, Shiraz University of Medical Sciences, Shiraz, Iran, 2014.

Sarrafzadeh, O., Talebi, A., MehriDehnavi, A., Moradia Amin, M., “The best descriptors for leukocytes detection in microscopic images of peripheral blood smear”, 1st National Conference on Microscopic Studies, Histomorphometry and Stereology Research Center, Shiraz University of Medical Sciences, Shiraz, Iran, 2014.

Momenzadeh, M., MehriDehnavi, A., Talebi, A., Sarrafzadeh, O., “Automatic recognition of candidiasis in microscopic images of Pop smear”,1st National Conference on Microscopic Studies, Histomorphome-try and Stereology Research Center, Shiraz University of Medical Sciences,

Shiraz, Iran, 2014.

Saeedizadeh Z, Talebi A, Mehri-Dehnavi A, Rabbani H, Sarrafzadeh O., “Extraction and Recognition of Myeloma Cell in Microscopic Bone Marrow Aspiration Images”, J Isfahan Med Sch 2015; 32(310), (2014).

Zahra Saeedizadeh, Alireza Mehri dehnavi, Ardeshir Talebi, Hossein Rabbani, Omid Sarrafzadeh, Alireza Vard, “Automatic Recognition of Myeloma Cells in Microscopic Images using Bottleneck algorithm, Modi-fied Watershed and SVM Classifier”, Journal of microscopy; doi: 10.1111/jmi.12314; 2015.

Maria Farahi, Hossein Rabbani, Ardeshir Talebi, Omid Sarrafzadeh, Shahab Ensafi, “segmentation of leishmania parasite in microscopic images using a modified chan-vese level set method”, 7th International conference on Graphic and Image Processing, ICGIP 2016, Singapore, 2015 (Accepted).

Omid Sarrafzadeh, Alireza Mehri Dehnavi, Hossein Rabbani , Narjes

Ghane, Ardeshir Talebi, “circlet based framework for red blood cells

segmentation and counting”, SiPS 2015, Hangzhou, China, 2015

(Accepted).

Omid Sarrafzadeh, Alireza Mehri Dehnavi, Hossein Rabbani , Ar-

deshir Talebi, “A simple and Accurate Method for White Blood Cells

Segmentation using K-Means Algorithm”, SiPS 2015, Hangzhou, China,

2015 (Accepted).

Omid Sarrafzadeh, Hossein Rabbani, Alireza Mehri Dehnavi, Ar-

deshir Talebi, “Detecting Different Sub-Types of Acute Myelogenous

Leukemia using Dictionary Learning and Sparse Representation”, ICIP

2015, Quebec, Canada, 2015 (Accepted).

Omid Sarrafzadeh, Alireza Mehri Dehnavi, “Nucleus and Cytoplasm

Segmentation in Microscopic Images Using K-means Clustering and Re-

gion Growing”, Journal of Advanced Biomedical Research, 4:174, 2015.

Omid Sarrafzadeh, Hossein Rabbani, Alireza Mehri Dehnavi, Ar-

deshir Talebi, “Analyzing features by SWLDA for the classification of HEp

-2 cell images using GMM”, Pattern Recognit. Let. (2016).

Feature Extraction and Classification

In a normal microscopic image, different cells and

patterns might be presented. In order to recognize cer-

tain cells within the image, supplementary methods,

such as, feature extraction and classification should be

developed. The most useful features include geometry

and texture features. After recognizing certain cells,

counting them through entire slid under microscope

might be done to provide a full report to pathologists. In

video processing of biological cells, more robust features

might be needed to report more useful information

about the cells such as the velocity, behavior, stage and

anomaly of different cells .