| SHORT COMMUNICATIONS |
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| Year : 2022 | Volume
: 12
| Issue : 1 | Page : 84-89 |
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Using marker-controlled watershed transform to detect Baker's cyst in magnetic resonance imaging images: A pilot study
Sadegh Ghaderi1, Kayvan Ghaderi2, Hamid Ghaznavi3
1 Department of Neuroscience and Addiction Studies, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, Iran
2 Department of Information Technology and Computer Engineering, Faculty of Engineering, University of Kurdistan, Sanandaj 66177-15175, Iran
3 Department of Radiology, Faculty of Paramedical Sciences, Kurdistan University of Medical Sciences, Sanandaj, Iran
Correspondence Address:
Hamid Ghaznavi
Department of Radiology, Faculty of Paramedical Sciences, Kurdistan University of Medical Sciences, Sanandaj
Iran
 Source of Support: None, Conflict of Interest: None
DOI: 10.4103/jmss.JMSS_49_20
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Nowadays, magnetic resonance imaging (MRI) has a high ability to distinguish between soft tissues because of high spatial resolution. Image processing is extensively used to extract clinical data from imaging modalities. In the medical image processing field, the knee's cyst (especially Baker) segmentation is one of the novel research areas. There are different methods for image segmentation. In this paper, the mathematical operation of the watershed algorithm is utilized by MATLAB software based on marker-controlled watershed segmentation for the detection of Baker's cyst in the knee's joint MRI sagittal and axial T2-weighted images. The performance of this algorithm was investigated, and the results showed that in a short time Baker's cyst can be clearly extracted from original images in axial and sagittal planes. The marker-controlled watershed segmentation was able to detect Baker's cyst reliable and can save time and current cost, especially in the absence of specialists it can help us for the easier diagnosis of MRI pathologies.
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