The cerebral vascular system is constituted by all the arteries and veins irrigating the brain. This vascular tree starts from two pairs of arteries, the vertebral arteries and the internal carotid arteries. These latter divide into a circular shape being called the Circle of Willis (CoW). There is considerable variability in the structure of the CoW among patients. The CoW can host various vascular diseases, among which intracranial aneurysms are of particular importance because their occurrence, or more precisely their rupture, can be devastating. Intracranial aneurysms often occur at the bifurcations of the arterial tree (saccular aneurysms), as a bulge in the vessel wall. It is crucial to recognize and monitor such aneurysms. Anatomical identification of the bifurcations of the CoW can be of great help to establish a diagnosis or to plan a surgical operation. In this study, we propose an automatic solution to categorize the vascular anatomy of the CoW in 3D volumes by identifying its main constituting bifurcations. Our solution combines machine learning and a multivariate analysis (Linear Discriminant Analysis: LDA). The LDA works as a classifier and reduces the dimensionality of the dataset by transforming the selected features in a lower dimensional space. This work is a preliminary study prior to moving to human cerebrovascular images. We evaluate the proposed method using several machine learning techniques combined with a leave-one-out validation applied on a set of 30 synthetic vascular images as well as 30 mouse cerebral vasculatures.
In this work, we aim to accurately segment the cerebral vasculature on MRI-TOF images. This study is part of a wider project1 in which we intend to characterize the arterial bifurcations in order to estimate the risk of occurrence of intra-cranial aneurysms (ICA). However, a very accurate segmentation of the vasculature is needed along the Circle of Willis (as this is where most of Intra-Cranial Aneurysms occur) prior to launch the bifurcation characterization. An imprecise segmentation of the Circle of Willis will inevitably lead to a deficient characterization, and thus an erroneous ICA risk estimation. This study was motivated by the lack of efficiency of various State of the Art segmentation methods. In this work, we try to mimic the behavior of the Human Visual System in order to correctly segment the Circle of Willis on TOF imaging of the brain. When Neuroradiologists diagnose an aneurysm on an MRI volume, they modulate the image contrast and luminance so that the vasculature is highlighted within the image. In this work, we first consider the display monitor behavior and we exploit a model that mimics the perception of contrasts by a human observer, in order to accentuate the vasculature for the last segmentation step. Indeed, thanks to this perceptual contrast enhancement, the amplitude of the vasculature moves beyond the rest of the image (parenchyma, cerebrospinal fluid,· · ·) this perceptual contrast stretching then allows to simplify the final thresholding step.
KEYWORDS: Aneurysms, Arteries, Blood vessels, 3D metrology, 3D acquisition, Brain, Blood circulation, Computed tomography, 3D image processing, Magnetic resonance imaging
An aneurysm is a vascular disorder represented by a ballooning of a blood vessel. The blood vessel’s wall is distorted by the blood flow, and a bulge forms there. When ruptured, the aneurysm may cause irreversible damage and could even lead to premature death. Intra-cranial aneurysms are the ones presenting the higher risks. In this work, thanks to a graph based approach, we detect the bifurcations located on the circle of Willis within brain mice cerebral vasculature. Once properly located in the 3D stack, we characterize the cerebral arteries bifurcations, i.e. we gather several properties of the bifurcation, such as their angles, or area cross section, in order to further estimate geometrical patterns that can favor the risk of occurrence of an intra-cranial aneurysm. Effectively, apart from genetic predisposition, and environmental risk factors (high blood pressure, smoking habits, ...) the anatomical disposition of the brain vasculature may influence the chances of an aneurysm to form. Our objectives in this paper is to obtain accurate measurements on the 3D bifurcations.
For every patient, nowadays, dentists use a software to generate the dental scheme. The dental scheme is basically a diagram representing the whole dentition of the patient. On this diagram, each tooth is represented along with the various operations the patient underwent. The dental scheme for instance shows whether some teeth are missing, or if any treatment was ever performed on the dental roots, it also represents the dental fillings, removable prosthesis, dental crowns or tooth bridges. Filling up the dental scheme may be tedious for dentists, as for every new patient, they would have to carefully make an inventory of every dental care the patient underwent. In this work, we intend to study the feasibility of automatically generating the dental scheme from radiographs. Indeed, we aim to propose an image processing method that would automatically detect missing teeth, as well as any dental care in the dentition, this may save a significant amount of time during the dental consultation. In a first step, our method extracts the relevant portion of the scanner image, i.e. we automatically crop the dentition and thus remove the jaws and chin. The bending of the jaw (dentition curvature) is also estimated, and allows to distinguish the upper and lower jaws. A local minimum/maximum computation coupled with the Hough transform, and a fit with Gaussian Mixture Models helps us to segment the teeth despite strong luminance irregularities due to the imaged spine.
KEYWORDS: Bone, 3D modeling, Anisotropy, Physiology, 3D image processing, Reconstruction algorithms, Tomography, 3D acquisition, Data acquisition, Wavelets, 3D image reconstruction, 3D microstructuring
Trabecular bone and its microarchitecture are of prime importance for health. This paper focuses onto the relationship between bone microarchitecture and the texture found on micro CT projections. From a small animal study, 5 mice legs were studied by microCT at a resolution of 6μm. The 3D reconstructions are only used as ground truth for their microarchitecture parameters. The study uses 2 different sets of tomographic data : 3 volumes acquired at ANU in Canberra and 2 volumes acquired in Nantes. For each projection set, we determine the texture orientation onto a ROI region of both medial epiphysis and diaphisys using a local variance computed onto Mojette projections from the ROI.
Carotid surgery is a frequent act corresponding to 15 to 20 thousands operations per year in France. Cerebral perfusion has to be tracked before and after carotid surgery. In this paper, a diagnosis support using quality metrics is proposed to detect vascular lesions on MR images. Our key stake is to provide a detection tool mimicking the human visual system behavior during the visual inspection. Relevant Human Visual System (HVS) properties should be integrated in our lesion detection method, which must be robust to common distortions in medical images. Our goal is twofold: to help the neuroradiologist to perform its task better and faster but also to provide a way to reduce the risk of bias in image analysis. Objective quality metrics (OQM) are methods whose goal is to predict the perceived quality. In this work, we use Objective Quality Metrics to detect perceivable differences between pairs of images.
Trabecular bone and its micro-architecture are of prime importance for health. Changes of bone micro-architecture are linked to different pathological situations like osteoporosis and begin now to be understood. In a previous paper, we started to investigate the relationships between bone and vessels and we also proposed to build a Bone Atlas. This study describes how to proceed for the elaboration and use of such an atlas. Here, we restricted the Atlas to legs (tibia, femur) of rats in order to work with well known geometry of the bone micro-architecture. From only 6 acquired bone, 132 trabecular bone volumes were generated using simple mathematical morphology tools. The variety and veracity of the created micro-architecture volumes is presented in this paper. Medical application and final goal would be to determinate bone micro-architecture with some angulated radiographs (3 or 4) and to easily diagnose the bone status (healthy, pathological or healing bone...).
Trabecular bone and its micro-architecture are of prime importance for health. Changes of bone micro-architecture are linked to different pathological situations like osteoporosis and begin now to be understood. In a previous paper [12], we started to investigate the relationships between bone and vessels and proposed some indices of characterization for the vessels issued from those used for the bone. Our main objective in this paper is to qualify the classical values used for bone as well as those we proposed for vessels according to different acquisition parameters and for several thresholding methods used to separate bone vessels and background. This study is also based on vessels perfusion by a contrast agent (barium sulfate mixed with gelatin) before euthanasia on rats. Femurs and tibias as well as mandibles were removed after rat’s death and were imaged by microCT (Skyscan 1272, Bruker, Belgium) with a resolution ranging from 18 to 3μm. The so obtained images were analyzed with various softwares (NRecon Reconstruction, CtAn, and CtVox from Bruker) in order to calculate bone and vessels micro-architecture parameters (density of bone/blood within the volume), and to know if the results both for bone and vascular micro-architecture are constant along the chosen pixel resolution. The result is clearly negative. We found a very different characterization both for bone and vessels with the 3μm acquisition. Tibia and mandibles bones were also used to show results that can be visually assessed. The largest portions of the vascular tree are orthogonal to the obtained slices of the bone. Therefore, the contrast agent appears as cylinders of various sizes.
Trabecular bone and its microarchitecture are of prime importance for health. Studying vascularization helps to better know the relationship between bone and vascular microarchitecture. This research is an animal study (nine Lewis rats), based on the perfusion of vascularization by a contrast agent (a mixture of 50% barium sulfate with 1.5% of gelatin) before euthanasia. The samples were studied by micro CT at a resolution of 9μm. Softwares were used to show 3D volumes of bone and vessels, to calculate bone and vessels microarchitecture parameters. This study aims to understand simultaneously the bone microarchitecture and its vascular microarchitecture.
Bone microarchitecture is the predictor of bone quality or bone disease. It can only be measured on a bone biopsy, which
is invasive and not available for all clinical situations. Texture analysis on radiographs is a common way to investigate
bone microarchitecture. But relationships between three-dimension histomorphometric parameters and two-dimension
texture parameters are not always well known, with poor results. The aim of this paper is twofold : to study one classical
parameter namely the fractal dimension which is easily computed on the 2D binary texture and to explore its
relationships with the microarchitecture. We performed several experiments in order to check from ground truth the
different possible values and their possible explanations. The results show great variations of the fractal dimension
according to the size of the window and its location. These variations can be explained both by a misuse of the algorithm
and by the number of trabecular and their characteristics inside the window where the fractal dimension is computed.
This study also shows a specific interest to work with dual fractal dimension of the bone-spongious tissues.
Given an image of a rough surface texture, the approach described here can estimate the direction from which the surface was lit. Unlike previous work, we require neither surface isotropy nor that the texture is included in the training set. The approach is based on active basis and the Mojette transform. The Mojette transform is used to estimate the orientation of the texture; it does so by finding which training samples have similar orientation features. The active basis model is then learned from training images by the shared pursuit algorithm. Next, the base histograms of the test image and textures with similar orientation features in the training set are compared so that the illumination directions can be estimated by minimizing their correlation coefficients.
This paper presents a hybrid watermarking technique which mixes additive and multiplicative watermark embedding
with emphasis on its robustness versus the imperceptibility of the watermark. The embedding is performed
in six wavelet sub-bands using independently three embedding equations and two parameters to modulate the
embedding strength for multiplicative and additive embedding. The watermark strength is independently modulated
into distinct image areas. Specifically, when a multiplicative embedding is used, the visibility threshold
is first reached near the image edges, whereas using an additive embedding technique the visibility threshold is
first reached into the smooth areas. A subjective experiment has been used to provide the optimal watermark
strength for three distinct embedding equations. Observers were asked to tune the watermark amplitude and to
set the strength at the visibility threshold. The experimental results showed that using an hybrid watermarking
technique significantly improves the robustness performance. This work is a preliminary study for the design of
an optimal wavelet domain Just Noticeable Difference (JND) mask.
This work is motivated by the limitations of statistical quality metrics to assess the quality of images distorted
in distinct frequency ranges. Common quality metrics, which basically have been designed and tested for various
kind of global distortions, such as image coding may not be efficient for watermarking applications, where
the distortions might be restricted on a very narrow portion of the frequency spectrum. We hereby want to
propose an objective quality metric whose performances do not depend on the distortion frequency range, but
we nevertheless want to provide a simplified objective quality metric in opposition to the complex Human Visual
System (HVS) based quality metrics recently made available. The proposed algorithm is generic (not designed
for a particular distortion), and exploits the contrast sensitivity function (CSF) along with an adapted Minkowski
error pooling. The results show a high correlation between the proposed objective metric and the mean opinion
score (MOS) given by observers. A comparison with relevant existing objective quality metrics is provided.
In the last decade digital watermarking techniques have been devised to answer the ever-growing need to protect the
intellectual property of digital still images, video sequences or audio from piracy attacks. Because of the proliferation of
watermarking algorithms and their applications some benchmarks have been created in order to help watermarkers
comparing their algorithms in terms of robustness against various attacks (i.e. Stirmark, Checkmark). However, no equal
attention has been devoted to the proposition of benchmarks tailored to assess the watermark perceptual transparency. In
this work, we study several watermarking techniques in terms of the mark invisibility through subjective experiments.
Moreover, we test the ability of several objective metrics, used in the literature mainly to evaluate distortions due to the
coding process, to be correlated with subjective scores. The conclusions drawn in the paper are supported by extensive
experimentations using both several watermarking techniques and objective metrics.
Regarding the important constraints due to subjective quality assessment, objective image quality assessment has recently been extensively studied. Such metrics are usually of three kinds, they might be Full Reference (FR), Reduced Reference (RR) or No Reference (NR) metrics. We focus here on a new technique, which recently appeared in quality assessment context: data-hiding-based image quality metric. Regarding the amount of data to be transmitted for quality assessment purpose, watermarking based techniques are considered as pseudo noreference metric: A little overhead due to the embedded watermark is added to the image. Unlike most existing techniques, the proposed embedding method exploits an advanced perceptual model in order to optimize both the data embedding and extraction. A perceptually weighted watermark is embedded into the host image, and an evaluation of this watermark allows to assess the host image's quality. In such context, the watermark robustness is crucial; it must be suffciently robust to be detected after very strong distortions, but it must also be suffciently fragile to be degraded along with the host image. In other words, the watermark distortion must be proportional to the image's distortion. Our work is compared to existing standard RR and NR metrics in terms of both the correlation with subjective assessment and of data overhead induced by the mark.
This paper describes a new kind of use for image watermarking. A stream watermarking method is presented, in which a key allows the authorized users to recover the original image. Our algorithm exploits the redundancy properties of the Mojette Transform. This transform is based on a specific discrete version of the Radon transform with an exact inversion. Anyone whom knows the watermark key will be able to decode the original image whereas only a marked image can be decoded without this key. The presented algorithm is suitable for different applications when fragile and reversible watermarks are mandatory such as medical image watermarking, and it could also be used for a data access scheme (cryptography). A multiscale watermark variation is presented and can be used when different user profile levels are encountered.
This paper describes a new methodology for image watermarking which is suitable both for copyright protection and for data hiding. The two presented algorithms are based upon the morphological mathematics properties of the Mojette Transform (denoted as MT in the following). The main properties of the Mojette transform are roughly recalled and the linked concept of phantom which depicts the null space of the operator is presented. Theses phantoms are implemented in the spatial domain giving the added watermarks. Then, two algorithms are presented based on this type of marks, the first one is devoted to the copyright embedding process and the second describes the steganographic scheme. Corresponding extractions of either the mark or the hidden message are then described. Finally, results are given in the last section for the two above schemes and robustness characteristics for the first scheme in terms of geometric attacks as well as the data hiding capacity for the second algorithm are discussed.
The work presented here deals with watermarking algorithms. The goal is to show how the Human Visual System (H.V.S) properties can be taken into account in the conception of such algorithms. The construction of the watermarking algorithm presented in this paper needs three steps. In the first one the selection of auspicious sites for the watermark embedding is described. The selection exploits a multi-channel model of the Human Visual System which decomposes the visual input into seventeen perceptual components. Medium and high frequencies are then selected to generate a sites map. This latter is improved by considering some high level uniform areas. The second step deals with the choice of the strength to apply to the selected sites. The strength is determined by considering the H.V.S. sensitivity to the local band limited contrast. In the third step, examples of spatial watermarking embedding and extraction are given. The same perceptual mask has been successfully used in other studies. The watermark results from a binary pseudo-random sequence, of length 64, which is circularly shifted so as to occupy all the sites mentioned above. The watermark extraction exploits the detection theory and requires both the perceptual mask and the original watermark. The extracted watermark is then compared to the original and a normalized correlation coefficient is computed. This coefficient value allows the detection of the copyright.
Video (and other multimedia sources) distribution starts to implement industrial solutions that supposes no quality of service (QoS) properties for the network. To overcome congestion problems in the core of a worldwide Internet network, mirrors sites at the edges of the network are dispatched. Thus the QoS problem is only relevant for the network extremities. Nevertheless, this strategy implies to replicate the multimedia database (denoted at MDB) at multiple edge points to meet the real-time constraints and to establish specific mechanisms between mirror sites to satisfy customer needs as for video distribution. For each of both kind of constraints, we propose a unique data/network representation.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.