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The use of computer technology in medical sciences is spreading with technology. The use of computers especially for imaging has become a third eye for physicians. In orthopedic surgeons, after simple roentgenograms for fracture detection, the use of computerized tomography and magnetic resonance has provided great convenience in the detection of fracture, typing, and therefore the appropriate treatment...
Three-dimensional X-Ray Micromotomography (3D μCT) has become an important tool to investigate bone morphology. Several investigators have searched a standard method for determining the optimal threshold value (optimal TH) to segment microtomographic images and quantify the bone morphology. The Conventional methods are based on subjective methods, and it is possible to obtain under or overestimated...
A reliable method to evaluate and follow the course of arthritis is given by examination of the carpal bones within the wrist joint. Humans typically have eight such small angular bones arranged in two rows. The small size as well as the number make manual segmentation for an analysis of the disease progression a tedious process. Further, fully automatic approaches are still not very reliable. To...
In the human body knees are most complex and delicate joints. Knee joints are frequently injured and damaged due to articulations. The knees are among the joints most commonly affected by osteoarthritis (OA). Articular Cartilage is a hard but slippery coating on the end of each bone which forms the joint. Cartilage breaks down and wears away in OA. In this work, image processing techniques are applied...
The segmentation of bones in the knee region is one of the first essential steps to perform further analysis, classification and osteoarthritis imaging biomarkers discovery. In this paper, an efficient graph-cut based segmentation algorithm is proposed. One of the challenges in current graph-cut schemes is properly distinguishing between regions of interest (ROI) and background regions with features...
To effectively diagnose and monitor the treatment of diseases such as osteoarthritis, the segmentation, processing and analysis of mass volumes of medical images is gaining high importance. In this paper, a new fully automated content-based segmentation framework is proposed. The framework is designed to be compatible with a wide variety of segmentation techniques. To this end, a novel content-based...
A key parameter in metabolic and pathologic studies is the estimation of body tissue distribution. This is a laborious and operator-dependent process. In this work we introduce an unsupervised muscle and fat quantification algorithm based on water only, fat only and water-and-fat MRI images of the mid-thigh area. We first use parametric deformable models to segment the subcutaneous fat and then apply...
We present an automated algorithm which classifies periprosthetic tissues in CT scans of patients with loosened hip prostheses. To our knowledge this is the first application of CT voxel classification to periprosthetic tissues of the hip. We use several image features including multi-scale image intensity, multi-scale image gradient and distance metrics. Seven classifier types were trained using...
The detection of cartilage loss due to disease progression in Osteoarthritis remains a challenging problem. We have shown previously that the sensitivity of detection from 3D MR images can be improved significantly by focusing on regions of `at risk' cartilage defined consistently across subjects and time-points. We define these regions in a frame of reference based on the bones, which requires that...
This paper is focused on the analysis of biomedical images, including textured ones. A segmentation method, based on network of synchronized oscillators is presented. Oscillator networks can be considered as a special case of the CNN. Its oscillatory dynamics allows encoding the different features of objects forming the visual scene, thus makes these network suitable for medium level image processing,...
The paper describes a set of approaches and routines designed to improve results in CT based 3D subtractive angiography of lower extremities via better global locally defined image data registration. Starting from the generic concept of 3D disparity-based flexible registration, modifications of this idea are made founded on prior anatomical knowledge, as segmentation into individual bone areas, their...
In this paper, we propose a fully automatic method to segment bone compartments in magnetic resonance (MR) images of knee joints gathered from a public database for research on knee osteoarthritis (OA), the osteoarthritis initiative (OAI). Considering the fixed scanning parameters which include position and flexion of the knee joint, the proposed method efficiently utilizes both shape and intensity...
Extraction of fetal biometric parameters for accurate estimation of gestational age using class separable shape sensitive segmentation scheme is presented in this paper. The class separability is achieved by introducing a perturbation with an appropriate cost functional associated to the image. The algorithm has been used to segment the gestational sac, yolk sac, femur bone and the parietal bones...
In this paper we propose a method to enhance Active Shape Model based bone segmentation. One major weakness of the classic algorithm is the use of a single dedicated image feature. However to model the variation of image content along the object boundaries it is more suitable to use different features for different regions. We derive an automatic intelligent selection of these features and integrate...
Computed tomography (CT) is used for the attenuation correction of positron emission tomography (PET) to enhance the efficiency of data acquisition process and to improve the quality of the reconstructed PET data in the brain. Due to the use of two different modalities, chances of misalignment between PET and CT images are quite significant. The main cause of this misregistration is the motion of...
Recent improvements of fetal MRI acquisitions now allow three-dimensional segmentation of fetal structures, to extract bio-metrical measures for pregnancy follow-up. Automation of the segmentation process remains a difficult challenge, given the complexity of the fetal organs and their spatial organization. As a starting point, we propose in this paper a fully automated segmentation method to localize...
Counting of different classes of white blood cells in bone marrow smears can give pathologists valuable information regarding various hematological disorders. For automation imaging analysis techniques, precise segmentation of white blood cells is quite challenging due to the complex contents in bone marrow smears. Far more different from traditional color imaging analysis methods, we introduced multispectral...
The segmentation of bones in computed tomography (CT) images is an important step for the simulation of forearm bone motion, since it allows to include patient specific anatomy in a kinematic model. While the identification of the bone diaphysis is straightforward, the segmentation of bone joints with weak, thin, and diffusive boundaries is still a challenge. We propose a graph cut segmentation approach...
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