Keywords: Liver, LiverAccurate detection of focal liver lesions in Gd-DTPA-enhanced magnetic resonance imaging (MRI) necessitates a high level of skill and experience. This task is typically performed by radiologists through visual inspection, which is time-consuming, labor-intensive, and subject to intra- and inter-observer variation. Convolutional neural networks (CNNs) have demonstrated significant potential in detecting lesions on medical imaging. Our study presents a unified multi-sequence lesion detector model for automatically detecting focal liver lesions on Gd-DTPA-enhanced MR images to aid in treatment decision-making.
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