Professor Hariton Costin
The “Gr.T. Popa” University of Medicine and Pharmacy, IASI
Faculty of Medical Bioengineering
ROMANIA
E-mail: hcostin@gmail.com

Abstract: Medical imaging mainly manages and processes missing, ambiguous, complementary, redundant and distorted data and information has a strong structural character. The understanding of any image involves the matching of features extracted from the image with pre-stored models. The production of a high-level symbolic model requires the representation of knowledge about the objects to be modeled, their relationships, and how and when to use the information stored within the model.
This presentation reports new (semi)automated methods for the segmentation and classification of images of cerebral structures using an information fusion technique based on soft computing (fuzzy logic) and specific knowledge. Fuzzy logic acts as a unified framework for representing and processing both numerical and symbolic information (“hybridization”), as well as structural information constituted mainly by spatial relationships in biomedical imaging. Our applications are mainly for the segmentation of brain structures for magnetic resonance (MR) and CT (computer tomography) images, based both on atlas and real data. Promising results show the superiority of this knowledge-based approach over best traditional techniques in terms of segmentation errors. The classification of different cerebral structures is made by implementing rules yielded both by domain literature and by medical experts. Though the proposed methodology has been implemented and successfully used for model-driven in the domain of MR and CT imaging, the deployed methods are generic and applicable to any structure that can be defined by expert knowledge and morphological images.
Another branch of applications of soft-computing and data fusion is represented by medical image registration, e.g. for PET and CT images. We first apply a mutual information based registration algorithm and then fuse the PET and CT images (taken separately or yielded by a PET-CT scanner) by using the 2ν-Granular Support Vector Machine. The fused image contains the properties of both PET and CT images and is an efficicient tool for image registration.

Brief Biography of the Speaker:
Prof. dr. eng. Hariton Costin, BS in Electronics and Telecommunications (1980), Ph.D. in Applied Informatics, MBA diploma, is full professor and chief of the Medical Electronics Department at the University of Medicine and Pharmacy / Faculty of Medical Bioengineering, Iasi, Romania, (www.umfiasi.ro). Also, he is senior researcher at the Romanian Academy, Institute for Computer Science – Iasi Branch, within the Image Processing and Pattern Recognition Lab, (http://www.iit.tuiasi.ro/personal/h_costin.html), where he studies image processing and analysis by using Artificial Intelligence methods and data fusion.
Competence areas include: medical electronics, biosignal and image processing and analysis, artificial intelligence (soft-computing, expert systems), hybrid systems, HCI (human-computer interfaces), telemedicine and e-health.
Scientific activity can be resumed by about 95 published papers (26 in Romania and 69 abroad), 5 books, 4 book chapters in foreign publishing houses, 3 patents, 2 national awards.
Research activity: 28 research reports, technical manager within FP5/INES 2001-32316 project, for a telemedicine application (www.euroines.com ; „Medcare” project); responsible for the first Romanian pilot telemedical centre in Iasi, (CEEX programme – research of excellence - www.mct-excelenta.ro and for the National Programme for R&D 2007-2013, www.cnmp.ro), director for 5 national granted projects in bioengineering and (biomedical) image processing / analysis, invited postdoc researcher at the University of Science and Technology of Lille (France, 2002, medical imaging), invited talks at international conferences.
Prof. Costin is a member of the I.E.E.E./Engineering in Medicine & Biology Society (EMBS) and of other 8 scientific societies.