New H3D-MarNet framework enhances CT image quality for radiotherapy

Researchers have developed H3D-MarNet, a novel two-stage framework designed to improve CT image quality for radiotherapy. The system first suppresses metal artifacts using wavelet-based denoising and then transforms kilo-voltage CT (kVCT) images to mega-voltage CT (MVCT) using a hybrid CNN and transformer architecture. This approach aims to enhance diagnostic accuracy and radiotherapy planning by preserving anatomical details and ensuring spatial coherence across slices, demonstrating significant improvements in PSNR and SSIM metrics. AI

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IMPACT Improves medical imaging analysis for radiotherapy, potentially leading to more accurate cancer treatment planning.

RANK_REASON The cluster contains an academic paper detailing a new technical approach. [lever_c_demoted from research: ic=1 ai=1.0]

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• H3D-MarNet
• CT
• radiotherapy
• kVCT
• MVCT
• CNN
• transformer
• Mubashara Rehman

• paper
• other