Skip to main content

Dr. Gurcan is a Guest Editor for IEEE Transactions on Medical Imaging for special issue on Multivariate Microscopy Image Analysis

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 above but also in the new and rapidly evolving field of systems biology since the MMI data unfolds the spatial information on the molecular level that cannot be evaluated using the classic "omics" methods. Although there has been great progress in the development and application of image analysis in biomedicine over the recent years, there are a number of significant challenges involving the MMI data. These challenges include acquisition, efficient storage, registration, segmentation, classification, semantic annotation and visualization of the MMI data. Recent advances in other related areas such as image processing, computer vision, pattern recognition, and machine learning as well as the availability of high-performance computing equipment at a relatively affordable cost are seemingly fueling the development of computational methods to deal with these challenges.

(http://www.ieee-tmi.org/CallForPapers.html).

This Special Issue will highlight new research directions in Multivariate Microscopy Image Analysis by collecting selected papers in all relevant areas including, but not limited to, the following topics:


  • Registration, segmentation, classification, retrieval

  • Object detection/classification/quantification

  • Computer-aided diagnosis and grading

  • Visualization

  • System evaluation

  • Novel computational architectures

  • Other related aspects

Comments

Post a Comment

Popular posts from this blog

CIALAB encouraging talented young minds with summer internships

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...
1 comment
Read more

Dr. Gurcan to present a tutorial at IEEE ICASSP 2010

Dr. Gurcan will present a tutorial at IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP) 2010 entitled “Biomedical Image Processing and Analysis Techniques.” ( http://www.icassp2010.org/Tutorial_03.asp) Biomedical image processing and analysis requires coordinated efforts of medical professionals, algorithmic and software engineers, and statisticians. Basic image processing techniques are frequently used in every aspect of the development from initial pre-processing techniques for noise reduction, to segmentation of lesions, to registration of lesions. Recent advances in hardware and software have made it possible to create digital scans of whole slides. These images are relatively large (100k x 100k) and in color, hence processing them present new challenges. Similarly, new computed tomography and magnetic resonance imaging scanners produce thousands of slices of images. The processing need for these images are enormous. Although biomedical image analy...
Post a Comment
Read more

Meniscus research to be presented at 2009 OARSI World Congress on Osteoarthritis

CIALAB work detailing relationships between the meniscus and cartilage, and their implications in the development and progression of osteoarthritis, has been accepted for presentation at the 2009 OARSI World Congress on Osteoarthritis. The analysis was performed by Jeff Prescott, Furqan Haq PhD, Tom Best MD/PhD, Micheal Pennell PhD, Rebecca Jackson MD, and Metin Gurcan PhD. The full abstract appears below. Purpose : To determine associations between meniscus volume and knee cartilage morphological measurements in subjects with osteoarthritis (OA). Methods : All data was obtained from the Osteoarthritis Initiative’s (OAI) public use dataset (www.oai.ucsf.edu). A sample of progression subjects produced by the OAI was used for the study (Subgroup B, release 0.B.2). Out of the 160 subjects in the sample, two had no discernable meniscus and were excluded, leaving 158 subjects in the analysis. The current study focused on the right knee, as this was the only knee for which cartilage measur...
1 comment
Read more