Segmentation of Liver Tumor in CT Scan Using ResU-Net

نویسندگان

چکیده

Segmentation of images is a common task within medical image analysis and necessary component segmentation. The segmentation the liver tumors an important but challenging stage in screening diagnosing diseases. Although many automated techniques have been developed for tumor segmentation; however, still due to fuzzy & complex background position with other organs. As result, creating considerable tumour division from CT scans critical identifying cancer. In this article, deeply dense-network ResU-Net architecture implemented on scan using 3D-IRCADb01 dataset. An essential feature residual block U-Net architecture, which extract additional information input data compared traditional network. Before being fed deep neural network, pre-processing are applied, including augmentation, Hounsfield windowing unit, histogram equalization. network performance evaluated dice similarity coefficient (DSC) metric. system connections outperformed state-of-the-art approaches identification, DSC value 0.97% organ recognition 0.83% methods.

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ژورنال

عنوان ژورنال: Applied sciences

سال: 2022

ISSN: ['2076-3417']

DOI: https://doi.org/10.3390/app12178650