Glial brain tumor detection by using symmetry analysis

Valentina Pedoia; Elisabetta Binaghi; Sergio Balbi; Alessandro De Benedictis; Emanuele Monti; Renzo Minotto

doi:10.1117/12.910172

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24 February 2012 Glial brain tumor detection by using symmetry analysis

Valentina Pedoia, Elisabetta Binaghi, Sergio Balbi, Alessandro De Benedictis, Emanuele Monti, Renzo Minotto

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Proceedings Volume 8314, Medical Imaging 2012: Image Processing; 831445 (2012) https://doi.org/10.1117/12.910172
Event: SPIE Medical Imaging, 2012, San Diego, California, United States

Abstract

In this work a fully automatic algorithm to detect brain tumors by using symmetry analysis is proposed. In recent years a great effort of the research in field of medical imaging was focused on brain tumors segmentation. The quantitative analysis of MRI brain tumor allows to obtain useful key indicators of disease progression. The complex problem of segmenting tumor in MRI can be successfully addressed by considering modular and multi-step approaches mimicking the human visual inspection process. The tumor detection is often an essential preliminary phase to solvethe segmentation problem successfully. In visual analysis of the MRI, the first step of the experts cognitive process, is the detection of an anomaly respect the normal tissue, whatever its nature. An healthy brain has a strong sagittal symmetry, that is weakened by the presence of tumor. The comparison between the healthy and ill hemisphere, considering that tumors are generally not symmetrically placed in both hemispheres, was used to detect the anomaly. A clustering method based on energy minimization through Graph-Cut is applied on the volume computed as a difference between the left hemisphere and the right hemisphere mirrored across the symmetry plane. Differential analysis involves the loss the knowledge of the tumor side. Through an histogram analysis the ill hemisphere is recognized. Many experiments are performed to assess the performance of the detection strategy on MRI volumes in presence of tumors varied in terms of shapes positions and intensity levels. The experiments showed good results also in complex situations.

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Valentina Pedoia, Elisabetta Binaghi, Sergio Balbi, Alessandro De Benedictis, Emanuele Monti, and Renzo Minotto "Glial brain tumor detection by using symmetry analysis", Proc. SPIE 8314, Medical Imaging 2012: Image Processing, 831445 (24 February 2012); https://doi.org/10.1117/12.910172

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