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 13 th , 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/
2
Embed
Microscopic Image Analysis th, 2013 with the Research Center · Microscopic Image Analysis Research Center Preprocessing ... Talebi, A., ^Extraction of Nucleolus andidate Zone in
This document is posted to help you gain knowledge. Please leave a comment to let me know what you think about it! Share it to your friends and learn new things together.
Transcript
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-
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).