Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/23616
Title: | A Three-Dimensional Reconstruction Integrated System for Brain Multiple Sclerosis Lesions | Authors: | Gregoriou, Charalambos Loizou, Christos P. Georgiou, Andreas Pantzaris, Marios C. Pattichis, Constantinos S. |
Major Field of Science: | Engineering and Technology | Field Category: | Medical Engineering | Keywords: | Magnetic resonance imaging;Multiple sclerosis;3D lesions reconstruction;Integrated system | Issue Date: | Sep-2021 | Source: | 19th International Conference on Computer Analysis of Images and Patterns, 2021, 28-30 September, Virtual Event | Start page: | 266 | End page: | 276 | Conference: | International Conference on Computer Analysis of Images and Patterns | Abstract: | In the course of a human brain acquisition, which is acquired by a magnetic resonance imager (MRI), two-dimensional (2D) slices of the brain are captured. These have to be aligned and reconstructed to a three-dimensional (3D) volume, which will better assist the doctor in following up the development of the disease. In this study, a 3D reconstruction integrated system for MRI brain multiple sclerosis (MS) lesion visualization is proposed. Brain MRI images from 5 MS subjects were acquired at four diffident consecutive time points (TP1-TP4) with an interval of 6–12 months. MS lesions were manually segmented by an expert neurologist and semi-automatically by a system and reconstructed in a brain volume. The proposed system assists the doctor in following up the MS disease progression and provides support to better manage the disease. The proposed system includes a 5-stage investigation (pre-processing, lesion segmentation, 3D reconstruction, volume estimation and method evaluation), as well as a module for the quantitative evaluation of the method. Twenty MRI images of the brain were used to evaluate the proposed system. Results show that the 3D reconstruction method proposed in this work, can be used to differentiate brain tissues and recognize MS lesions by providing improved 3D visualization. These preliminary results provide evidence that the proposed system could be applied in the future in clinical practice given that it is further evaluated on more subjects. | URI: | https://hdl.handle.net/20.500.14279/23616 | ISBN: | 978-3-030-89128-2 | DOI: | 10.1007/978-3-030-89128-2_26 | Rights: | © Springer | Type: | Conference Papers | Affiliation : | Cyprus University of Technology Cyprus Institute of Neurology and Genetics University of Cyprus |
Publication Type: | Peer Reviewed |
Appears in Collections: | Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation |
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