Clinical Image Analysis

CIALAB is pleased to introduce the three interns namely Tong Gan, Rosana Rodriguez Milanes and Michael Priddy working through summer’09. Rosana Rodriguez Milanes - I am a third year undergraduate student in Electronic Engineering from Universidad del Norte, Colombia. My experience as a volunteer foreign student in the Clinical Image Analysis Laboratory has been an edifying, gratifying and enriching. Being able to participate, to learn and to collaborate in the Clinical Image Analysis Laboratory during the past two weeks has allowed me to improve my analytical and interpretative skills in processing histopathological and MRI images. I have been able to learn about segmentation, region growing, splitting and merging algorithms development. I have also had the privilege of knowing and interacting with excellent engineers who have helped me improve my skills as a foreign student. I am grateful for the opportunity that the Ohio State University has given me to collaborate and to learn with

Jeff Prescott, a student in the CIALAB, has had his work accepted as a regular paper to the 24th International Symposium on Computer and Information Sciences. The work, entitled "Template-Based Level Set Segmentation using Anatomical Information: Application to Quadriceps Muscles in MR Images from the Osteoarthritis Initiative", describes a method for the semi-automated segmentation of quadriceps muscles. Abstract: We present a preliminary evaluation of an automated segmentation method of the quadriceps muscles from MR images of the thigh. The method is being developed to assist research into morphological properties of the quadriceps muscles as biomarkers of osteoarthritis (OA) incidence and progression. Our method uses an anatomically anchored, template-based initialization of the level set-based segmentation approach. A template image is selected using the Kullback-Leibler divergence measure based on the muscle and fat content of the thigh images. Contours of the quadr

Analysis of microscopy images of samples has numerous applications in a wide range of areas such as molecular biology, life sciences, pharmacology and medicine. Recently, new protocols based on molecular labeling and imaging automation are spurring a revolution in microscopy techniques since they allow to capture the trans- or co-localization of proteins in multivariate microscopy image (MMI) data. In MMI, each pixel at a location may be associated with more than one intensity value, to an array of multiple intensities. These intensities can encode protein location, co-location or translocation over time, as seen by incident light of multiple wavelengths. In histopathology, for example, diagnosis and grading of cancer and other diseases can be improved by analyzing localization patterns in MMI obtained with multi-staining and/or multi-spectral techniques. As a consequence, there is a rapidly growing interest in the processing and analysis of MMI not only in the classic fields listed ab

CIALAB members Dr. Kamel Boussaid, Dr. Erkan Mumcuoglu, Olcay Sertel, and Jeff Prescott have had their recent work accepted for presentation at EMBC 2009, taking place September 2-6 in Minneapolis, Minnesota. The accepted papers are: Prescott JW, Swanson MS, Haq F, Best TM, Powell K, Jackson R, Gurcan MN, "An Automated Method for Femur Segmentation for Osteoarthritis Research." Prescott JW, Priddy M, Swanson MS, Haq F, Best TM, Powell K, Jackson R, Gurcan MN, "An Automated Method for Intramuscular Fat Detection in Quadriceps Muscles for Osteoarthritis Diagnosis." Belkacem-Boussaid K, Sertel O, Lozanski G, Shana’aah A, Gurcan MN, "Extraction of color features in the spectral domain to recognize centroblasts in histopathology." Samsi S, Krishnamurthy AK, Groseclose M, Caprioli RM, Lozanski G, Gurcan MN, "Imaging Mass Spectrometry Analysis for Follicular Lymphoma" Mumcuoglu EU, Prescott J, Baker BN, Clifford B, Long F, Castile R, Gurcan MN, "Im