转发:数学与数据科学应用研究所系列报告: Adaptive Weighted Curvature-based Active Contour for Medical Image Segmentation

发布者:李君钰发布时间:2023-05-18浏览次数:10

报告人:       庞志峰教授(河南大学数学与统计学院)

报告日期: 2023年5月19日 

报告时间: 15:00-17:00

报告地点: 励学楼B 219

邀请人:    杨建斌


报告摘要Image segmentation is a complex and core technique for disease diagnosis or image-guided surgery in the medical image domain. However, low-quality images, such as images with weak edges and intensity inhomogeneities, may bring considerable challenges for radiologists. In this paper, we propose an adaptive weighted curvature-based active contour model by coupling heat kernel  convolution and adaptively weighted high-order total variation for medical image segmentation to improve diagnosis effectiveness. To reduce the computational complexity, the heat kernel convolution operation is applied to approximate the perimeter of a segmentation curve. In addition, the weighted parameter included in the high-order total variation term can be automatically evaluated based on an adaptive input image to emphasize local structures and increase segmentation accuracy. Since the proposed method is a smoothing optimization model, the alternating direction method of multipliers is introduced to translate the original problems into several easily solvable subproblems. The numerical experimental results on ultrasonic and MRI datasets demonstrate that the proposed model is quite efficient and robust compared with several traditional segmentation methods.

报告人简介 庞志峰河南大学教授博士生导师河南省应用数学中心(河南大学)副主任河南省数字图形图像学会副理事长南洋理工大学/香港城市大学博士后利物浦大学访问学者主持国家自科和省部级项目共计3参与973项目1省重大和重点项目各1校企合作项目2目前兼任《CT理论与应用研究》编委会委员,《中国体视学与图像分析》编委会委员授权国家发明专利2发表学术论文40余篇。


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