Growing experience with the liver splitting technique and favorable results equivalent to those of whole liver transplant have led to wider application of split liver transplantation(SLT) for adult and pediatric recip...Growing experience with the liver splitting technique and favorable results equivalent to those of whole liver transplant have led to wider application of split liver transplantation(SLT) for adult and pediatric recipients in the last decade. Conversely, SLT for two adult recipients remains a challenging surgical procedure and outcomes have yet to improve. Differences in organ shortages together with religious and ethical issues related to cadaveric organ donation have had an impact on the worldwide distribution of SLT. Despite technical refinements and a better understanding of the complex liver anatomy, SLT remains a technically and logistically demanding surgical procedure. This article reviews the surgical and clinical advances in this field of liver transplantation focusing on the role of SLT and the issues that may lead a further expansion of this complex surgical procedure.展开更多
This paper presents a fully automatic segmentation algorithm based on geometrical and local attributes of color images. This method incorporates a hierarchical assessment scheme into any general segmentation algorithm...This paper presents a fully automatic segmentation algorithm based on geometrical and local attributes of color images. This method incorporates a hierarchical assessment scheme into any general segmentation algorithm for which the segmentation sensitivity can be changed through parameters. The parameters are varied to create different segmentation levels in the hierarchy. The algorithm examines the consistency of segments based on local features and their relationships with each other, and selects segments at different levels to generate a final segmentation. This adaptive parameter variation scheme provides an automatic way to set segmentation sensitivity parameters locally according to each region's characteristics instead of the entire image. The algorithm does not require any training dataset. The geometrical attributes can be defined by a shape prior for specific applications, i.e. targeting objects of interest, or by one or more general constraint(s) such as boundaries between regions for non-specific applications. Using mean shift as the general segmentation algorithm, we show that our hierarchical approach generates segments that satisfy geometrical properties while conforming with local properties. In the case of using a shape prior, the algorithm can cope with partial occlusions. Evaluation is carried out on the Berkeley Segmentation Dataset and Benchmark (BSDS300) (general natural images) and on geo-spatial images (with specific shapes of interest). The F-measure for our proposed algorithm, i.e. the harmonic mean between precision and recall rates, is 64.2% on BSDS300, outperforming the same segmentation algorithm in its standard non-hierarchical variant.展开更多
文摘Growing experience with the liver splitting technique and favorable results equivalent to those of whole liver transplant have led to wider application of split liver transplantation(SLT) for adult and pediatric recipients in the last decade. Conversely, SLT for two adult recipients remains a challenging surgical procedure and outcomes have yet to improve. Differences in organ shortages together with religious and ethical issues related to cadaveric organ donation have had an impact on the worldwide distribution of SLT. Despite technical refinements and a better understanding of the complex liver anatomy, SLT remains a technically and logistically demanding surgical procedure. This article reviews the surgical and clinical advances in this field of liver transplantation focusing on the role of SLT and the issues that may lead a further expansion of this complex surgical procedure.
文摘This paper presents a fully automatic segmentation algorithm based on geometrical and local attributes of color images. This method incorporates a hierarchical assessment scheme into any general segmentation algorithm for which the segmentation sensitivity can be changed through parameters. The parameters are varied to create different segmentation levels in the hierarchy. The algorithm examines the consistency of segments based on local features and their relationships with each other, and selects segments at different levels to generate a final segmentation. This adaptive parameter variation scheme provides an automatic way to set segmentation sensitivity parameters locally according to each region's characteristics instead of the entire image. The algorithm does not require any training dataset. The geometrical attributes can be defined by a shape prior for specific applications, i.e. targeting objects of interest, or by one or more general constraint(s) such as boundaries between regions for non-specific applications. Using mean shift as the general segmentation algorithm, we show that our hierarchical approach generates segments that satisfy geometrical properties while conforming with local properties. In the case of using a shape prior, the algorithm can cope with partial occlusions. Evaluation is carried out on the Berkeley Segmentation Dataset and Benchmark (BSDS300) (general natural images) and on geo-spatial images (with specific shapes of interest). The F-measure for our proposed algorithm, i.e. the harmonic mean between precision and recall rates, is 64.2% on BSDS300, outperforming the same segmentation algorithm in its standard non-hierarchical variant.
