Fusion-Based Deep Learning for Kidney Stone Detection Using Ultrasound, CT, and MRI

  • Unique Paper ID: 168103
  • Volume: 11
  • Issue: 4
  • PageNo: 1251-1254
  • Abstract:
  • Kidney stone detection using medical imaging techniques such as ultrasound (US) and computed tomography (CT) is a critical diagnostic task. Ultrasound is safe but lacks the contrast needed for reliable stone detection, while CT provides higher accuracy but exposes patients to radiation. In this study, we propose a multimodal learning approach that fuses data from both ultrasound and CT/MRI to improve detection rates, reduce false positives/negatives, and leverage the strengths of both imaging techniques. Our approach employs a dual-branch deep learning architecture, combining U-Net for ultrasound image segmentation with a ResNet-based model for CT/MRI data. We demonstrate that multimodal fusion significantly enhances kidney stone detection accuracy

Cite This Article

  • ISSN: 2349-6002
  • Volume: 11
  • Issue: 4
  • PageNo: 1251-1254

Fusion-Based Deep Learning for Kidney Stone Detection Using Ultrasound, CT, and MRI

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