The paper presents an automatic method for liver vasculature segmentation in volumetric images obtained during Computed Tomography (CT) patient examination. The method, apart from the CT image, also requires an additional image containing binary liver mask. A modified multiscale vesselness filter (VF) performs vasculature detection. VF response is used to determine the starting voxels for the s...

Vessel segmentation is a key step for various medical applications, such as diagnosis assistance, quantification of vascular pathology, and treatment planning. This paper describes an automatic vessel segmentation framework which can achieve highly accurate segmentation even in regions of low contrast and signal-to-noise-ratios (SNRs) and at vessel boundaries with disturbance induced by adjacen...

We present a fully automated method for top-down segmentation of the pulmonary arterial tree in low-dose thoracic CT images. The main basal pulmonary arteries are identified near the lung hilum by searching for candidate vessels adjacent to known airways, identified by our previously reported airway segmentation method. Model cylinders are iteratively fit to the vessels to track them into the l...

A fully automated, robust vessel segmentation algorithm has been developed for choroidal OCT, employing multiscale 3D edge filtering and projection of "probability cones" to determine the vessel "core", even in the tomograms with low signal-to-noise ratio (SNR). Based on the ideal vessel response after registration and multiscale filtering, with computed depth related SNR, the vessel core estim...

In this paper, different approaches are discussed for medical image segmentation. These are based on thresholding, learning, modeling and automatic fuzzy method. Segmentation techniques, discussed under these approaches are used in different applications. In identification of brain lesions, vessel lumen segmentation and histopathology cancer image segmentation. Further used in tissue segmentati...