The article introduces a novel implicit neural representation (INR) architecture for compressing volumetric medical images. It addresses the challenges of high-resolution image storage and manipulation in the medical imaging field. The proposed architecture combines Lanczos downsampling, SIREN deep network, and SRDenseNet upsampling to reduce training time, increase compression rate, and save GPU memory. Experimental results show higher quality reconstruction and faster training speed compared to existing techniques. The study uses CT scan slices from the Visible Human project dataset for evaluation.
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by Armin Sheiba... a las arxiv.org 03-14-2024
https://arxiv.org/pdf/2403.08566.pdfConsultas más profundas