Self-assessed Contrast-Maximizing Adaptive Region Growing
نویسندگان
چکیده
In the context of an experimental virtual-reality surgical planning software platform, we propose a fully self-assessed adaptive region growing segmentation algorithm. Our method successfully delineates main tissues relevant to head and neck reconstructive surgery, such as skin, fat, muscle/organs, and bone. We rely on a standardized and selfassessed region-based approach to deal with a great variety of imaging conditions with minimal user intervention, as only a single-seed selection stage is required. The detection of the optimal parameters is managed internally using a measure of the varying contrast of the growing regions. Validation based on synthetic images, as well as truly-delineated real CT volumes, is provided for the reader’s evaluation.
منابع مشابه
Maximal Contrast Adaptive Region Growing for CT Airway Tree Segmentation
We introduce a self-assessed region growing technique capable of producing airway segmentations with reasonable quality. The main advantages of our technique are its robustness against leakage, and the absence of any training stages. Our method can not be considered fully automatic as it requires manual seeding of the trachea region, although there exists a variety of techniques to circumvent t...
متن کاملSelf-Learning Model-Based Segmentation of Medical Images
Interaction increases flexibility of segmentation but it leads to undesirable behaviour of an algorithm if knowledge being requested is inappropriate. In region growing, this is the case for defining the homogeneity criterion, as its specification depends also on image formation properties that are not known to the user. We developed a region growing algorithm that learns its homogeneity criter...
متن کاملImplementation and Analysis of Contrast Enhancement Techniques for Medical Images
Image enhancement which is one of the significant techniques in digital image processing plays important role in many fields. Image enhancement improves the visual appearance of an image or to convert an image to a form better suited for analysis by a human or machine. Contrast enhancement is one of the commonly used image enhancement method to improve the quality of image. In this paper, adapt...
متن کاملAdaptive Region Growing Based on Boundary Measures
Weak boundary contrast, inhomogeneous background and overlapped intensity distributions of the object and background are main causes that may lead to failure of boundary detection for many image segmentation methods. An adaptive region growing method based on multiple boundary measures is presented. It consists of region expansion and boundary selection processes. During the region expansion pr...
متن کاملA New Region Growing Segmentation Algorithm for the Detection of Breast Cancer
As medical images are mostly fuzzy in nature, segmenting regions based intensity is the most challenging task. Segmentation of medical images using seeded region growing technique is increasingly becoming a popular method because of its ability to involve high-level knowledge of anatomical structures in seed selection process. In this paper, we have made improvements in region growing image seg...
متن کامل