Skip to main content

New Post Doctoral, one doctoral, and two graduate Researchers have joined the CIALAB!

Khaldi Niazi, a post-doctoral researcher, Li Mao, a doctoral researcher, Furkan Keskin, a graduate researcher, and Evgenios Kornaropoulos, a graduate researcher, have joined the CIA Lab. Khalid Niazi has been involved since February. Li Mao will be involved from February, 2012 until January, 2013. Furkan Keskin will be involved from March, 2012 until May, 2012. Evgenios Kornaropoulos will be involved March until August 2012. Khalid is a post-doctoral researcher from Uppsala University in Sweden. Khalid will be involved with the development of non-linear filtering methods of medical images. Li is currently a PhD candidate in the School of Electronics and Information at Northwestern Polytechnical University and his visit is funded by Xi'an University of Architecture and Technology and the China State Administration of Foreign Experts Affairs. Li will be involved with digital watermarking and digital image processing. Furkan is a visiting researcher currently pursuing a Masters degree in the Department of Electrical and Electronics Engineering at Bilkent University in Ankara, Turkey. His studies include cancer cell image classification, follicular lymphoma grading, and complex wavelets and their applications. Evgenios is a graduate researcher from the Centre for Research and Technology Hellas / Informatics and Telematics Institute (CERTH - ITI), located in Thessaloniki, Greece. He is involved with biological image processing and analysis, computer vision, signal processing in electrophysiology (especially in electroencephalography, EEG), brain mapping, human computer interfaces, and brain computer interfaces.

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

Recent publications

The CIA lab has recently had 4 articles published in PLOS One and the Journal of Urology. Automated Staging Of T1 Bladder Cancer Using Digital Pathologic H&E Images: A Deep Learning approach (Journal of Urology). The paper discusses the need for accurately gauging tumor cell intrusion into Lamina Propria in an effort to substage bladder cancer. It explains how transfer learning in conjunction with Convolutional Neural Networks can be used to accurately identify different bladder layers and then compute the distance between tumor nuclei and Lamina Propria. The article is available here:  https://www.jurology.com/article/S0022-5347(18)41148-2/pdf Identifying tumor in pancreatic neuroendocrine neoplasms from Ki67 images using transfer learning (PLOS One). This paper examines a proposed methodology to automatically differentiate between NET and non-tumor regions based on images of Ki67 stained biopsies. It also uses transfer learning to exploit a rich set of features ...
6 comments
Read more