Spectral factor analysis for multi-isotope imaging in nuclear medicine

Abstract. In nuclear medicine, simultaneous dual-isotope imaging is used to determine the distribution of two radiotracers from a single acquisition and for emission/transmission (E/T) imaging in SPECT. However, no general solution to the cross-talk problem caused by scattered and unscattered photons has been found yet and accurate quantification cannot be performed. We describe a general method of spectral factor analysis (SFA) for multi-isotope acquisitions. SFA corrects for cross-talk due to unscattered and scattered photons in planar or SPECT imaging involving two or more radiotracers and for E/T scans. A Tc-99m/I-123 phantom study shows that quantitative accuracy is within 10% with SFA, while errors up to 170% are observed using conventional spectral windows

Recurrence of destructive periodontal disease after treatment. A long term study

This study demonstrates the difficulties which arise in statistical analysis derived from data of observations in post-treatment healing and recurrence of periodontal disease. Ten individuals received an initial phase of treatment followed by surgical pocket elimination utilizing replaced flap surgery. Clinical measurements of recession and pocketing were taken pre-operatively and 6 monthly thereafter for a period of four years after treatment. The results have shown that surgical treatment is least benefit in cases of mild pocketing, and of most benefit in cases of severe pocketing. A tendency for reduction in recession levels after two years was observed. Pocketing and attachment levels showed a tendency toward relapse as early as 6 months postoperatively. However, this simple observation masks a complex pattern of tissue remodeling in which some sites remain stable, others improve, while others relapse with time. Improvement may occur concurrently in different sites. Continued improvement in the clinical parameters of pocketing and attachment levels was observable in some sites for up to 2 years after surgery, after which the tendency for recurrent disease became more noticeable. Analyses of changes in attachment levels may be misleading, because they may mask the divergent or convergent trends of recession and pocketing, which may be occurring simultaneously. As bursts of healing as well as bursts of destruction could be observed concurrently over the period of 4 years after treatment, it is suggested that a state of «dynamic equilibrium» is established, in which continued tissue remodeling over a protracted period of time, may give rise to the clinical misconception that little or no changes are occurring in the majority of sites with time.Cette étude démontre les difficultés qui surviennent dans l’analyse statistique issue des données et observations obtenues après traitement, au cours de la guérison et pendant les récidives de la paradontite. Dix patients ont subi une phase initiale de traitement suivie d’une élimination chirurgicale des poches paradontales utilisant le «flap surgery» (rétablissement de la partie recouvrante de la gencive). On a relevé des mesures précises des récessions et des poches paradontales avant l’intervention chirurgicale ainsi que tous les six mois pendant quatre ans. Les résultats ont démontré que dans les cas de paradontite peu sévères, les avantages sont considérables. On a aussi observé une tendance générale à la réduction des niveaux de récession pendant deux ans. On a noté une tendance vers la rechute dès six mois après l’opération. Cette observation d’ordre général déguise cependant un mode complexe d’évolution où certaines zones se stabilisent, d’autres s’améliorent et d’autres se détériorent avec le temps. Le processus d’amélioration peut exister simultanément dans différentes zones. On a pu observer l’amélioration continue des paramètres cliniques des poches et des attachements jusqu’à deux ans après l’intervention chirurgicale, après quoi le síndrome resurgit. Les tendances divergentes ou convergentes simultanées de la récession ainsi que de la formation des poches sont difficiles à observer seulement par des analyses de changement des niveaux d’attachement.Puisqu’il a été possible d’observer des poussées d’amélioraton et de régression pendant quatre ans après le traitement, on peut conclure qu’un état «d’équilibre dynamique» s’établit, dans lequel un remodelage continu du tissu gingival pendant une période prolongée pourrait conduire à la conception erronée que très peu ou même aucun changement ne se produit avec le temps dans la majorité des zones observées

Wavelet analysis of the liver from CT datasets

In this paper a feasibility study of liver CT dataset classification, using features from different scales of the wavelet transform analysis in conjunction with statistical pattern recognition methods is presented. In our study 850 extracted sub-images from 19 liver CT scans were used. Statistical measurements were collected; from the sub-images as well as from their different scale wavelet transform coefficients. We found by using the Leave-One-Out method that the combination of the features from the first and second Order statistics, achieved overall classification accuracy >90.0, both specificity and sensitivity >90.0. Features selected by the spatial domain performed better than the wavelet based techniques, under the classification rule of Quadratic Classifier (QC). In addition, features selected by the third scale wavelet transform coefficients performed better than those collected from the other wavelet scales, under the classification rule of Bayesian Classifier (BC)

The non-uniformity of imaging devices and its impact in quantitative studies

info:eu-repo/semantics/publishe

Computer Aids for Decision-Making in Radiology

This paper describes two prototype applications built using the workstation, one in mammography and the other using X-ray CT images in the management of neuroblastoma. 1. GENERIC ARCHITECTURE The central element of the radiology workstation is a decision procedure based on a model of decision-making and implemented as a logic program. The model consists of a set of logical rules for constructing arguments for and against candidate solutions. Originally developed by Fox and co-workers [4], the model has been successfully used in prototypes of clinical tools [5] and found to be applicable to a wide range of clinical decisions, providing a readily understood mechanism for selecting and presenting information which is relevant to a specific decision. We have applied the model to diagnostic radiology, extending it to include a set of rules which embody a model of radiological image interpretation. Fox's original decision procedure was used to reason about alternative decision options ("candidates ") by constructing lines of reasoning for and against each of the candidates ("arguments"). Arguments are constructed by applying information in a general medical knowledge base to the contents of an individual patient record. Our extended procedure allows evidence obtained from operations on digital images to be incorporated

Automatic segmentation of liver using a topology adaptive snake

Most attempts at automatic segmentation of liver from computerised tomography images to date have relied on low-level segmentation techniques, such as thresholding and mathematical morphology, to obtain the basic liver structure. The derived boundary can then be smoothed or refined using more advanced methods. In this paper we present a method by which a topology adaptive active contour model, or snake, accurately segments liver tissue from CT images. The use of conventional snakes for liver segmentation is difficult due to the presence of other organs closely surrounding the liver. Our technique avoids this problem by adding an inflationary force to the basic snake equation, and initialising the snake inside the liver. Once the user has initialised the snake for one CT slice, the starting locations for other slices in a dataset are determined automatically from the center of gravity of the segmented area of previous slice. We present results from over 500 images, covering 4 different healthy datasets, and each liver slice is segmented in 2D before being compared to the equivalent segmentation performed by hand. Statistical analysis of the datasets shows that, in each case, there is no significant difference between the areas and the snake-segmented liver to the areas of hand segmented liver, here treated as the gold standard

Automatic 3D segmentation of the liver from computed tomography images, a discrete deformable model approach

Automatic segmentation of the liver has the potential to assist in the diagnosis of disease, preparation for organ transplantation, and possibly assist in treatment planning. This paper presents initial results from work that extends on previous two-dimensional (2D) segmentation methods by implementing full three-dimensional (3D) liver segmentation, using a self-reparameterising discrete deformable model. This method overcomes many of the weaknesses inherent in 2D segmentation techniques, such as the inability to automatically segment separate lobes of the liver in each image slice, and sensitivity to individual-slice noise. Results are presented showing volumetric and overlap comparison of twelve automatically segmented livers with their corresponding manually segmented livers, which were treated as the gold standard for this study. © 2006 IEEE

Level set snake algorithms on the fetal heart

The fetal heart has very thin intra-chamber walls which are often not resolved by ultrasound scanners and may drop out as a result of imaging. In order to measure blood volumes from all chambers in isolation, deformable model approaches were used to segment the chambers and fill in the missing structural information. Three level set algorithms in the fetal cardiac segmentation literature (two without and, one with the use of a shape prior) were applied to real ultrasound data. The shape prior term was extracted from the shape prior level set and incorporated into the amorphous snakes for a fairer comparison. To our knowledge this is the first time these existing fetal cardiac non shape based segmentation algoridims have been modified for shape awareness in this way. © 2007 IEEE