Clinical Image Analysis

Dr. Gurcan's EUREKA (Exceptional, Unconventional Research Enabling Knowledge Acceleration) grant is discussed in a recent OSU research news article (http://researchnews.osu.edu/archive/2009eurekagrants.htm). Dr. Gurcan's Clinical Image Analysis Lab (www.bmi.osu.edu/cialab) is committed to developing imaging biomarkers for several diseases.

A method for the classification of Centrablast cells versus Non-Centroblast in Follicular Lymphoma has been accepted for publication in the Analytical and Quantitative Cytology and Histology journal. The authors of the paper were Kamel Belkacem-Boussaid, Ph.D, and Michael. Pennell, Ph.D, Gerard. Lozanski, MD, Arwa. Shanaah, MD, and Metin Gurcan, Ph.D. The title of the manuscript is "Computer-aided classification of centroblast cells in follicular lymphoma". The abstract of the manuscript appears below. Objective: In this paper, we develop a novel automated method to distinguish centroblast (CB) cells from non-centroblast (non-CB) cells in follicular lymphoma cases and measure its performance on cases obtained by a consensus of six pathologists. Study Design: Geometric and color texture features were used in the training and testing of the supervised quadratic discriminant analysis (QDA) classifier. The technique was trained and tested on a data set composed of 218 CB images a...

The 4th Annual International Scholar Research Exposition Opening Reception took place in Bricker Hall on November 19, 2009 at The Ohio State University. Posters documenting the research efforts of visiting scholars are on display throughout November and December in the 2nd Floor Lobby of Bricker Hall. Dr. Ahmet Alkan, an international scholar from Turkey, working at the CIALAB presented a poster at the exposition. The poster’s title is “Computerized Image Analysis of Thigh Muscles for Osteoarthritis.” President Gee and Dr. Whitacre, vice president for research, honored Dr. Alkan with a certificate. Ahmet Alkan received his Ph.D. in Electrical & Electronics Engineering from Sakarya University in 2005. He is funded by a fellowship from The Scientific and Technological Research Council of Turkey (TÜBİTAK) in 2009. He is currently a visiting scholar in the Department of Biomedical Informatics at The Ohio State University, working with Dr. Metin N. Gurcan. His research interests include...

Daniya Zamalieva, MS has joined the clinical image analysis group as a new Ph.D. student majoring in Computer Science and Engineering program. She received her B.S. degree in Computer Engineering in 2007 from Hacettepe University and M.S. degree in 2009 from Bilkent University, Turkey. During her graduate study, she was interested in Computer Vision and Pattern Recognition and she worked on processing and analysis of remotely sensed images. During her PhD studies, she will focus on computer-assisted diagnosis and creation of imaging biomarkers.

A method for the semi-automated segmentation of the meniscus in OAI images developed by the CIALAB Osteoarthritis Research Group has been accepted for publication in the Osteoarthritis and Cartilage Journal. The authors of the paper were Mark Swanson, a Medical Student with Roessler Scholarship, Jeff Prescott, an MD/PhD student in the lab, Thomas Best MD/PhD, Kimberly Powell, Rebecca Jackson MD, Furqan Haq PhD, and Metin Gurcan PhD. The abstract of the manuscript appears below. Abstract: Objective : The goal of this study was to develop an algorithm to semi-automatically segment the meniscus in a series of magnetic resonance (MR) images to use for normal knees and those with moderate osteoarthritis (OA). Method : The segmentation method was developed then evaluated on 10 baseline magnetic resonance images obtained from subjects with no evidence, symptoms, or risk factors of knee (OA), and 14 from subjects with established knee OA enrolled in the Osteoarthritis Initiative (OAI). Aft...

A method for the segmentation of the quadriceps muscles in OAI images developed by the CIALAB Osteoarthritis Research Group has been accepted for publication in the Journal of Digital Imaging. The authors of the paper were Jeff Prescott, an MD/PhD student in the lab, Thomas Best MD/PhD, Mark Swanson, Furqan Haq PhD, Rebecca Jackson MD, and Metin Gurcan PhD. The abstract of the manuscript appears below. Abstract: In this paper we present a semi-automated segmentation method for magnetic resonance (MR) images of the quadriceps muscles. Our method uses an anatomically anchored, template-based initialization of the level set-based segmentation approach. The method only requires the input of a single point from the user inside the rectus femoris. The templates are quantitatively selected from a set of images based on modes in the patient population, namely sex and body type. For a given image to be segmented, a template is selected based on the smallest Kullback-Leibler divergence betwee...

New research on the meniscus performed by the Osteoarthritis Research Group in the CIALAB and presented at the OARSI conference was highlighted in an article on docguide.com.