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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