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Photographic supra-projection is a forensic process that aims to identify a missing person from a photograph and a skull found. One of the crucial tasks throughout all this process is the craniofacial superimposition which is usually carried out manually by forensic anthropologists; thus being very time consuming and presenting several difficulties when trying to find a good fit between the 3D model...
Diabetic retinopathy is a complication of diabetes and early detection is essential for effective treatment. In this paper, a novel technique for the separation of normal and abnormal retinal images is described. Various features are extracted from local sub images and then fed through multiple classifiers to categorise them into interim classes followed by a reasoning process to give a more reliable...
Efficient optic disk (OD) localization and segmentation are important tasks in automated retinal screening. In this paper, we take digital curvelet transform (DCUT) of the enhanced retinal image and modify its coefficients based on the sparsity of curvelet coefficients to get probable location of OD. If there are not yellowish objects in retinal images or their size are negligible, we can then directly...
In this paper, we present two new filtered back-projection (FBP) type algorithms for cylindrical detector helical cone-beam geometry with no position dependent backprojection weight. The algorithms are extension of the recent exact Hilbert filtering based 2D divergent beam reconstruction with no back-projection weight to the FDK type algorithm for reconstruction in 3D helical trajectory cone-beam...
Daily volume loss of the residual limp is reported as one of the greatest challenges in socket fitting. Assisted vacuum socket systems were developed to prevent stump's volume loss and maintain sufficient socket fit. There is however very little quantitative biomechanical research for the evaluation of below knee sockets with assisted vacuum systems. Highly accurate in-vivo measurements became recently...
Ultrasound images segmentation is a difficult problem due to speckle noise, low contrast and local changes of intensity. Intensity based methods do not perform particularly well on ultrasound images. However, it has been previously shown that these images respond well to local phase-based methods which are theoretically intensity-invariant. Here, we use level set propagation to capture the left ventricle...
Segmented cross sectional MRI images were used to construct 3D virtual models of the carotid bifurcation in 5 healthy volunteers. Geometric features such as bifurcation angle, planarity angle, asymmetry angle tortuosity and curvature were calculated for the normal head posture and were compared to the equivalent values acquired with the head rotated clockwise by up to 80 degrees. The results obtained...
The presence of microcalcifications clusters, which appear as small bright spots in mammographic images, can be considered as a very important sign for breast cancer diagnosis. They can, however, be hard to detect due to their size and low contrast from surrounding normal tissue. In this paper, a new fuzzy-based method is presented to provide an appropriate segmentation of microcalcifications. This...
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...
Diagnosis of the underlying causes of widespread spinal pathologies such as back pain and whiplash remains problematic. Many studies suggest that segmental instability may occur and that the study of the intervertebral kinematics can be a valuable, objective method to assess spinal segment functionality. Direct measurement of the intervertebral kinematics results very invasive and unpractical; as...
This paper focuses on researches related to medical digital imaging of endoscopic gastritis. It provides suffice information on endoscopic procedure and types of gastritis. Besides that, it also briefly addressed feature extraction methods. Feature selection and Multiple Instance Learning (MIL) concept are also reviewed. As a conclusion, this paper become a basis to propose an improved artificial...
This paper presents a new wavelet domain adaptive despeckling technique for contrast enhancement of medical ultrasound (US) images for improving the clinical diagnosis. This method uses the Rayleigh distribution for modeling the speckle wavelet coefficients and the signal wavelet coefficients are approximated using the Gaussian distribution. Combining these as statistical priors, we have developed...
Truncated data problems are encountered in computed tomographic (CT) scanning scenarios where it is desirable to restrict the radiation dosage to a region-of-interest (ROI) of the object cross-section being imaged. In this paper, we propose a new image reconstruction technique for handling truncated data based on projection data extrapolation using a non-stationary time-series modeling approach. A...
Nowadays, medical diagnostics using images has a considerable importance in many areas of medicine. It promotes and makes easier the acquisition, transmission and analysis of medical images. The use of digital images for diseases evaluations or diagnostics is still growing up and new application modalities are always appearing. This paper presents a methodology for a semi-automatic segmentation of...
This work develops a microcalcifications' detection system in mammograms by using difference of Gaussians filters (DoG) and artificial neural networks (ANN). The digital image processing proposed show the basic wavelet-based behavior of DoG as a mother function frequently used in several vision tasks, and in this case, used in order to enhance the microcalcifications' traces in standard mammograms...
This work proposes a new restoration method to improve mammographic images by using Anscombe transform and Wiener filter to quantum noise reduction. Besides, it is performed an image enhancement by using a restoration inverse filter, calculated based on the image system modulation transfer function (MTF). This pre-processing technique were used for a set of mammographic phantom images in order measure...
Watershed transform on tensorial morphological gradient (TMG) is a new approach to segment diffusion tensor images (DTI). Since the TMG is able to express the tensorial dissimilarities in a single scalar image, the segmentation problem of DTI is then reduced to a scalar image segmentation problem. Therefore, it can be addressed by well-known segmentation techniques, such as the watershed transform...
In laser osteotomy bone is cut precisely with a laser. A robot is used to position an end-effector with a scanhead, which deflects the cutting laser. An optical tracking system (OTS) tracks the position of the bone, in our case a skull, and the end effector. The skull is registered to its model, based on a segmented CT data, as well as the robot to the OTS. With this a complete transformation chain...
This paper addresses a novel image thresholding scheme using Atanassov intuitionistic fuzzy set. The intuitionistic fuzzy set theory takes into account the membership degree and another uncertainty term , the non- membership degree. Non membership degree is calculated from Sugeno type intuitionistic fuzzy generator. The use of two uncertainties in the Atanassov's intuitionistic fuzzy set helps in...
The proposed mobile agent collects the load index and performs the distributed scheduling considering the behavior of the different kinds of applications. The environments obtained were considered due to the application of parallel processing of using medical images as well as the comparison of their performance time to measure them. The objective of this paper is to offer alternatives of processes...
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