Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/12532
Title: Brain Image and Lesions Registration and 3D Reconstruction in Dicom MRI Images
Authors: Loizou,  Christos P. 
Papacharalambous, Christos 
Samaras, Giorgos 
Kyriacou, Efthyvoulos C. 
Kasparis, Takis 
Pantziaris, Marios 
Eracleous, Eleni 
Pattichis, Constantinos S. 
Major Field of Science: Engineering and Technology
Field Category: Computer and Information Sciences;Electrical Engineering - Electronic Engineering - Information Engineering;MEDICAL AND HEALTH SCIENCES
Keywords: 3D-Reconstruction;Magnetic Resonance Imaging;Multiple sclerosis disease
Issue Date: 10-Nov-2017
Source: 30th IEEE International Symposium on Computer-Based Medical Systems, 2017, Thessaloniki, Greece, 22-24 June
Conference: IEEE International Symposium on Computer-Based Medical Systems 
Abstract: During a human brain MRI acquisition the resulting image is formed out of 2D slices. The slices must then be aligned and reconstructed to provide a 3-dimensional (3D) visualization of the brain volume. We propose in this work, an integrated system for the register ion and 3D reconstruction of DICOM MRI images and lesions of the brain acquired from multiple sclerosis (MS) subjects at two different time intervals (time 0 (T0) and time 1 (T1)). The system facilitates the follow up of the MS disease development and will aid the doctor to accurately manage the follow up of the disease. It involves a 6-stage analysis (preprocessing, lesion segmentation, registration, 3D reconstruction, volume estimation and method evaluation), as well as module quantitative evaluation of the method. The system was evaluated based on one MRI phantom and one DICOM MRI image of the brain. The accuracy of the proposed registration and reconstruction (- / -) method was 78.5%/97.2% and 95.4%/95.8% for the phantom and the MRI images respectively. These preliminary results provide evidence that the proposed system could be applied in future in the clinical practice.
ISSN: 2372-9198
DOI: 10.1109/CBMS.2017.53
Rights: © 2017 IEEE.
Type: Conference Papers
Affiliation : Cyprus University of Technology 
Frederick University 
Ayios Therissos Medical Diagnostic Center 
University of Cyprus 
Publication Type: Peer Reviewed
Appears in Collections:Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation

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