Skip to main content

Welcome Dr. Fazly Abas

The CIA Lab is proud to add the newest member to our lab, Dr. Fazly Salleh Abas.

Dr. Fazly Salleh Abas received his B.Eng degree in Electronic and Electrical Engineering from Strathclyde University, Scotland in 1999 and Ph.D in Electronics and Computer Science from University of Southampton, England in 2004 where he worked on a project involving content-based analysis and retrieval of craquelure (crack) patterns. He has been a faculty member at the Faculty of Engineering and Technology, Multimedia University, Malaysia since 1999 and is currently a visiting scholar at the Department of Biomedical Informatics, Ohio State University. His current research interests are in image/video processing, pattern recognition, biomedical informatics, motion analysis for sports and rehabilitation applications as well as having certain degree of involvement in biometrics research.

Comments

  1. UnknownMay 16, 2018 at 3:09 AM

    We developed our solutions based on understanding of the imaging clinical trial process & unfulfilled needs of the trial sponsor & various participants in the trials

    ReplyDelete

Post a Comment

Popular posts from this blog

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

Drs. Goceri, Kus, and Senaras Present at OSUMC Research Day

On April 25th, Drs. Goceri, Kus, and Senaras presented their research at the OSUMC Research Day.  Dr. Evgin Goceri presented “Automatic and Robust Segmentation of Liver and Its Vessels from MR Datasets for Pre-Evaluation of Liver Translation” which proposed a robust and fully automated method for segmenting the liver and its vessels from MR images. Dr. Goceri’s study presented a novel approach to reducing processing time by employing binary regularization of the level set function. The fully-automatic segmentation of liver and its vessels with the proposed method was more efficient than manual approach and the other methods in the literature in terms of processing time and accuracy. Dr. Pelin Kus presented “Segmentation and Quantification of Tissue Necrosis in Tuberculosis” which focuses on how the immune system of patients infected with M. tuberculosis responds by using many types of cells including macrophages that form granulomas within the pulmonary tissue. Segmentati...
3 comments
Read more

Drs. Abas, Goceri, and Kus Present Research at International Scholar Research Exposition

Out of more than 1,800 international visiting scholars at the Ohio State University, Dr. Abas of Malaysia and Drs. Goceri and Kus of Turkey were three of thirty-three finalists chosen to present their research at the International Scholar Research Exposition. The exposition recognizes the presence of visiting scholars on campus and their contribution to the university and global community. On November 20,2015, the Opening Reception of the 10 th Annual International Scholar Research Exposition was held for the finalists to present their research.  Their posters will be on display during November and December in Bricker Hall.   Dr. Abas’s poster was titled “Acne Image Analysis: Lesion Localization and Classification.” His research addressed the assessment of acne and used a computer-assisted image analysis approach to generate region-of-interest map for acne lesions as a preliminary step to count the number of lesions within a specific area. This research w...
Post a Comment
Read more