Deep learning aided prostate cancer detection for early diagnosis & treatment using MR with TRUS images

Although difficult, robust and reliable synchronization of multimodal medical pictures has several practical uses. For instance, in MR-TRUS fusing guided prostate treatments, picture registration between the two modalities is essential. However, due to the significant variety in image appearance and...

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Veröffentlicht in:Journal of intelligent & fuzzy systems 2024-01, Vol.46 (2), p.3395
Hauptverfasser: Sucharitha, G, sankardass, Veeramalai, Rani, R, Bhat, Nagaraj, Rajaram, A
Format: Artikel
Sprache:eng
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Zusammenfassung:Although difficult, robust and reliable synchronization of multimodal medical pictures has several practical uses. For instance, in MR-TRUS fusing guided prostate treatments, picture registration between the two modalities is essential. However, due to the significant variety in image appearance and correlation, MR-TRUS picture registration remains a challenging issue. In this research, we suggest employing deep convolutional neural networks (CNN) i.e. three dimensional CNN U-NET (3D-Conv-Net) to develop a resemblance measure for MR-TRUS registration. Finally, for the second-order optimal of the taught measure, we apply a composite optimisation method that searches the solution space for an appropriate starting point. We also use a multi-stage process to improve the optimisation metric.
ISSN:1064-1246
1875-8967
DOI:10.3233/JIFS-235744