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A novel framework for MR image segmentation and quantification by using MedGA.

Leonardo Rundo1, Andrea Tangherloni2, Paolo Cazzaniga3

  • 1Department of Informatics, Systems and Communication, University of Milano-Bicocca, Milan, Italy; Institute of Molecular Bioimaging and Physiology, Italian National Research Council, Cefalù, PA, Italy; Department of Radiology, University of Cambridge, Cambridge, UK; Cancer Research UK Cambridge Centre, Cambridge, UK.

Computer Methods and Programs in Biomedicine
|June 16, 2019
PubMed
Summary
This summary is machine-generated.

This study introduces an evolutionary framework to improve medical image segmentation accuracy for bimodal Magnetic Resonance (MR) images. The novel approach enhances image analysis, aiding physicians in diagnosis and treatment planning.

Failed At:

2026-06-19T13:47:37.150610+00:00

Keywords:
Adaptive thresholdingBimodal intensity distributionEvolutionary computationImage pre-processingMagnetic Resonance imagingQuantitative medical imaging

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