X-ray micro-tomography has become an essential tool to investigate the mechanical and physical properties of snow, which are tied to its microstructure. A crucial step in the 3D image processing is the binary segmentation of the grayscale X-ray attenuation coefficient image to a binary ice/pore image. In the snow community, this step is usually based on global thresholding conducted with smooth...

We present a new software package for interactive segmentation of 3D images by geodesic snakes, with manual editing. Several variants of level set snakes are incorporated, including both gradientmagnitude based snakes as well as region-competition snakes. A complete segmentation pipeline, including image preprocessing, bubble initialization and parameter control, is provided in an intuitive use...

this paper presents a new three-dimensional curvelet transform based dictionary learning for automatic segmentation of intraretinalcysts, most relevant prognostic biomarker in neovascular age-related macular degeneration, from 3d spectral-domain optical coherencetomography (sd-oct) images. in particular, we focus on the spectralis sd-oct (heidelberg engineering, heidelberg, germany) system, and...

Computer-aided detection and diagnosis (CAD) has been widely investigated to improve radiologists׳ diagnostic accuracy in detecting and characterizing lung disease, as well as to assist with the processing of increasingly sizable volumes of imaging. Lung segmentation is a requisite preprocessing step for most CAD schemes. This paper proposes a parameter-free lung segmentation algorithm with the...

  Introduction: The process of discriminating among benign and malignant hyperplasia begun with subjective methods using light microscopy and is now being continued with computerized morphometrical analysis requiring some features. One of the main features called Volume Percentage of Stroma (VPS) is obtained by calculating the percentage of stroma texture. Currently, this feature is calculated ...

Bayesian Ying-Yang(BYY) harmony learning system and theory is a new kind of statistical learning approach. It has shown great advantages of parameter learning and model selection on finite mixture modeling. In this paper, we extend the BYY learning system to multivariate t mixtures and propose a gradient BYY harmony learning algorithm for t mixtures. Via optimizing the harmony function, this al...

Recently, optimization with graph cuts became very attractive but generally remains limited to small-scale problems due to the large memory requirement of graphs, even when restricted to binary variables. Unlike previous heuristics which generally fail to fully capture details, [8] proposes another band-based method for reducing these graphs in image segmentation. This method provides small gra...

Segmentation is an important preprocessing step in many applications. Compared to colour segmentation, fusion of colour and depth greatly improves the segmentation result. Such a fusion is easy to do by stacking measurements in different value dimensions, but there are better ways. In this paper we perform fusion using the channel representation, and demonstrate how a state-of-the-art segmentat...

‎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...

Fingerprint image segmentation is part of pre-processing in fingerprint image recognition system. It has a critical effect to the fingerprint image recognition system. Regardless of years of research in the area of general purpose image segmentation, it is still a very challenging task. A new image decomposition scheme, called the Adaptive and Orientation algorithm, is proposed to achieve effec...