Bidirectional Evolution of Morphological Level Set for Fast Image Segmentation
نویسندگان
چکیده
We propose a novel level set method for fast image segmentation, which evolves level set functions using simple binary morphological operations. The proposed method is superior to a previously reported morphological level set method in capable of bidirectional evolution of level set functions, i.e., the interface of a level set function can either expand or shrink toward the object boundary. The experimental results on image segmentation show the high performance and fast computation of the proposed level set method, which also facilitates parallel hardware and optical implementation.
منابع مشابه
Partial Differential Equations applied to Medical Image Segmentation
This paper presents an application of partial differential equations(PDEs) for the segmentation of abdominal and thoracic aortic in CTA datasets. An important challenge in reliably detecting aortic is the need to overcome problems associated with intensity inhomogeneities. Level sets are part of an important class of methods that utilize partial differential equations (PDEs) and have been exte...
متن کاملA Method for Body Fat Composition Analysis in Abdominal Magnetic Resonance Images Via Self-Organizing Map Neural Network
Introduction: The present study aimed to suggest an unsupervised method for the segmentation of visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) in axial magnetic resonance (MR) images of the abdomen. Materials and Methods: A self-organizing map (SOM) neural network was designed to segment the adipose tissue from other tissues in the MR images. The segmentation of SAT and VA...
متن کاملFast Statistical Level Sets Image Segmentation for Biomedical Applications
In medical microscopy, image analysis offers to pathologist a modern tool, which can be applied to several problems in cancerology: quantification of DNA content, quantification of immunostaining, nuclear mitosis counting, characterization of tumor tissue architecture. However, these problems need an accurate and automatic segmentation. In most cases, the segmentation is concerned with the extr...
متن کاملBitplane Based Area Morphology for CBIR
Area morphology filters are capable of removing objects in an image based solely on the object area. These operators can be effectively used for content based image retrieval. However, the traditional level set based implementations of these operators are impractical because of their time complexities. Here we present a fast implementation of area morphology based on bitplane decomposition of t...
متن کاملAssessment of the Log-Euclidean Metric Performance in Diffusion Tensor Image Segmentation
Introduction: Appropriate definition of the distance measure between diffusion tensors has a deep impact on Diffusion Tensor Image (DTI) segmentation results. The geodesic metric is the best distance measure since it yields high-quality segmentation results. However, the important problem with the geodesic metric is a high computational cost of the algorithms based on it. The main goal of this ...
متن کامل