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2018.6.12 陈韵梅 教授:Edge Based Joint Multi-contrast MR Image Reconstruction

发布日期: 2018-06-11   浏览次数 105

报告题目: Edge Based Joint Multi-contrast MR Image Reconstruction

  人:陈韵梅 教授
  人:沈超敏 副教授
报告时间:2018612 周二 10:00-11:00
报告地点:中北校区理科大楼B816

 

报告人简介:

陈韵梅教授,现任Florida大学杰出教授。 曾获中华人民共和国国家自然科学三等奖、中华人民共和国教育部科技进步一等奖。最近五年来,陈韵梅教授主要致力于数学和图像科学这一交叉学科的研究。研究课题不仅包括图像分析中数学模型的建立与数值方法的发展,而且对其潜在的数学理论进行了进一步的探索。她在国际最顶尖成像期刊发表多篇具有重要影响的学术论文。陈韵梅教授被公认为偏微分方程与图像处理领域内的世界级科学家,在国际上具有崇高的学术地位。

 

报告摘要:

We propose a new joint image reconstruction method by recovering edge directly from observed data, then reconstructing images with their edge information. For joint edge reconstruction our model minimizes the fidelity term together with the matrix Frobeniun norm or spectral norm or nuclear norm across the contrasts and L1 norm over the pixels. Derivation of data fidelity for the Jacobian of multi-contrast images and transformation of noise distribution are also detailed. The new minimization problem yields an optimal O(1/k2) convergence rate, where k is the iteration number, and the per-iteration cost is low thanks to the close-form matrix-valued shrinkage.

The numerical results indicate that the proposed method improves reconstruction efficient and accuracy compared to the state-of-the-arts.