8 In this paper, we propose a new knowledge-based method illustrated in the context of segmentation, which labels 9 internal brain structures viewed by magnetic resonance imaging (MRI). In order to improve the accuracy of the la10 beling, we introduce a fuzzy model of regions of interest (ROI) by analogy with the electrostatic potential distribution, 11 to represent more appropriately the knowl...

GTS associates with every IF-sentence φ and suitable modelM a semantical game GM(φ), played by two players, one in the role of Verifier and one in the role of Falsifier. Moves in the game are choices for domain elements as assignments for the variables bound by the quantifiers ∃ (move for player in the role of Verifier) and ∀ (move for the player in the role of Falsifier) and choices for ‘left’...

High performance coding of image sequences requires efficient motion estimation and compensation. Block matching techniques are the usual choice. However they produce irregular motion fields and require subsequent regularization. This paper reports on a motion estimation technique that merges block matching with polynomial approximation and region growing to achieve such a regularization of the...

Vessel diameter is an important factor for indicating retinal microvascular signs. In automated retinal image analysis, the measurement of vascular width is a complicated process as most of the vessels are few pixels wide. In this paper, we propose a new technique to measure the retinal blood vessel diameter which can be used to detect arteriolar narrowing, arteriovenous (AV) nicking, branching...

Prostate segmentation in MRI may be difficult at the interface with the bladder where the contrast is poor. Coupled-models that segment simultaneously both organs with non-overlapping constraints offer a good solution. As a presegmentation of the structures of interest is required, we propose in this paper a fast deformable model to segment the bladder. The combination of inflation and internal...

We present a novel technique for the 3D segmentation of unknown objects from cluttered dual-energy Computed Tomography (CT) data obtained in the baggage security-screening domain. Initial materials-based coarse segmentations, generated using the Dual-Energy Index (DEI), are refined by partitioning at automatically-detected regions. Partitioning is guided by a novel random forest based quality m...

A computer system has been developed for evaluating the morphometrical feature extraction. The features are derived directly from a digital scan of breast fine needle biopsy slides. First the background elimination by thresholding hue component is applied, then the actual segmentation is done with region growing technique. The quality of feature space is measured with classifier based on nonpar...

Light Detection and Ranging (LiDAR), a high-precision technique used for acquiring three-dimensional (3D) surface information, is widely used to study surface vegetation information. Moreover, the extraction of a vegetation point set from the LiDAR point cloud is a basic starting-point for vegetation information analysis, and an important part of its further processing. To extract the vegetatio...

We present two approaches for automatically segmenting the spinal cord/canal from native CT images of the thorax region containing the spine. Different strategies are included to handle images where only part of the spinal column is visible. The algorithms require one seed point given on a slice located in the middle region of the spine, and the rest is automatic. The spatial extent of the spin...

A framework of fuzzy information fusion is proposed in this paper to automatically segment tumor areas of human brain from multispectral magnetic resonance imaging (MRI) such as T1-weighted, T2-weighted and proton density (PD) images. A priori knowledge about tumors described by radiology experts for different types of MRI are very helpful to guide a automatic and a precise segmentation. Howeve...