Paulina Mitrea

Abdominal Tumor Characterization and Recognition Using Superior-Order Cooccurrence Matrices, Based on Ultrasound Images

The noninvasive diagnosis of the malignant tumors is an important issue in research nowadays. Our purpose is to elaborate computerized, texture-based methods for performing computer-aided characterization and automatic diagnosis of these tumors, using only the information from ultrasound images. In this paper, we considered some of the most frequent abdominal malignant tumors: the hepatocellular carcinoma and the colonic tumors. We compared these structures with the benign tumors and with other visually similar diseases. Besides the textural features that proved in our previous research to be useful in the characterization and recognition of the malignant tumors, we improved our method by using the grey level cooccurrence matrix and the edge orientation cooccurrence matrix of superior order. As resulted from our experiments, the new textural features increased the malignant tumor classification performance, also revealing visual and physical properties of these structures that emphasized the complex, chaotic structure of the corresponding tissue.

Modelling cutaneous senescence process

During the last years, skin aging has become an area of increasing research interest. High frequency ultrasound allows the “in vivo” appreciation of certain histological parameters and offers new characteristic markers, which may quantify the severity of the cutaneous senescence process. This paper focuses on measuring the changes in skin thickness and dermis echogenicity , as part of the complex ageing process, on different intervals of age. In particular by using a multiscale approach we will compute some parameters which are connected with complexity (fractal structure) of skin ageing.

Iterative Methods for Obtaining Energy-Minimizing Parametric Snakes with Applications to Medical Imaging

After a brief survey on the parametric deformable models, we develop an iterative method based on the finite difference schemes in order to obtain energy-minimizing snakes. We estimate the approximation error, the residue, and the truncature error related to the corresponding algorithm, then we discuss its convergence, consistency, and stability. Some aspects regarding the prosthetic sugical methods that implement the above numerical methods are also pointed out.

Texture-Based Methods and Dimensionality Reduction Techniques Involved in the Detection of the Inflammatory Bowel Diseases from Ultrasound Images

The inflammatory bowel diseases (IBD) are severe, chronic and recurring disorders, requiring continuous patient monitoring. The most reliable methods for the diagnosis of the inflammatory bowel diseases are invasive (endoscopy, colonoscopy, histopathology) or irradiating (CT). We aim to develop computerized methods for the noninvasive assessment of the bowel inflammation level based on information obtained from ultrasound images. In this work, we study the role of the textural parameters in characterizing different types of inflammatory bowel diseases and the colorectal tumors. The dimensionality reduction techniques are taken into consideration in order to obtain the relevant textural features and to improve the result of the automatic diagnosis. The Principal Component Analysis (PCA) method and the Correlation based Feature Selection (CFS) method, as well as their combinations, are assessed for this purpose. The methods of Support Vector Machines (SVM) and Multilayer Perceptron (MLP), which gave very good results in our former experiments, are implemented for the automatic diagnosis. B-mode ultrasound images belonging to biopsied patients, are used. The patients were suffering from the following types of diseases: Crohn’s disease, ulcerative recto-colitis, colo-rectal cancer.

Multi-resolution analysis, numerical methods and reverse dynamics, integrated in software instruments for performance improving in the satellite remote sensing

In this paper we present the general conception and the mathematical background of a software environment aimed to provide enhanced remotely-sensed images processing capabilities. Integral and discrete transforms, multi-resolution analysis, reverse dynamics, symbolic computation principles and tools are involved. As mathematical background, this paper presents some details concerning discrete transforms, multi-resolution analysis, and reverse dynamics

Semantic investigation of a control-flow subset of BPMN 2.0

Business Process Model and Notation (BPMN), now at version 2.0.2, provides a standard graphical representation for specifying business processes. In this paper we report on the first stage of a semantic investigation of BPMN, using methods in the tradition of programming languages semantics. We consider a control-flow subset of BPMN and an execution architecture based on an intermediate language that we name ℒBPMN. The execution architecture comprises two main components: a translator which takes as input a BPMN model and generates ℒBPMN code, and an interpreter for ℒBPMN. ℒBPMN is a process oriented imperative language providing a combination of concepts, including maximal parallelism and durational activities. We employ the mathematical methodology of metric semantics in designing and relating an operational semantics O and a denotational semantics D for ℒBPMN. We establish the formal relation between O and D by using an abstraction operator and a fixed point argument. In this way we prove the correctness of the denotational semantics with respect to the operational semantics. We focus on the semantic investigation of BPMN. We also explain how the operational semantics can serve as a blueprint for an implementation on a client-server architecture.

Diseased tissue area detection and delimitation, by fusion between finite difference methods and textural analysis

The basic goals of this paper target on the development and implementation of algorithms which provide the energy-minimizing snakes in parametric form, then in applying them to textural analysis based medical diagnosis. In order to derive these algorithms, we focus on Finite Differences Methods (Explicit and Crank-Nicolson Finite Difference Schemes), widely used in medical image processing applications. We examine the consistency, stability, and convergence rate, proving their increased quality able to provide maximum accuracy when determining the diseased anatomic tissue delimitation in the context of medical images.

Mathematical Methods for Assessing the Prognostic of Fixed Partial Dentures Resulting from Evaluating a Group of Dental Patients in Romania

Based on some mathematical and statistical approaches, our study leads to some conclusions concerning the procedures related to the orodental prosthetics. Occlusal equilibration in orodental prosthetics is a major issue because besides motivating patients for a regular daily oral hygiene, it could significantly increase the longevity of FPR. More dental hygiene information should be given after prosthetic treatment and patients should be motivated to attend recalls on a regular basis for professional teeth-cleaning. Interdental cleaning aids should be explained and the patients have to be motivated to use them at least once a day and the using technique should be individualized. Regarding the application of the deformable models theory, implemented in the context of an expert type software environment, it is known that the fact that modelling by advanced methods and techniques based on the deformable surfaces theory increases the efficiency of the dentofacial prosthetics procedures is a domain of great interest in the actual medical research.

Finite difference based algorithms for optimal snakes used in medical diagnosis

In this paper, we describe briefly the 2D parametric deformable models, then we infer an algorithm, via Crank-Nicolson finite difference scheme for finding the so-called energy-minimizing (i.e. optimal) snake. The residue, the truncature - error and the order of accuracy related to this algorithm are estimated, in order to establish its consistency. We prove that the algorithm leads to better results regarding its convergence than the algorithm developed by the explicit finite difference scheme. Some aspects concerning the computerized assistance, that implement this algorithm in both prosthetic surgical methods and medical treatment monitoring in Metabolic Syndrome, are also pointed out.

On the Approximation-Error of Some Numerical Methods for Obtaining the Optimal Deformable Model

This paper deals with two approximation methods for obtaining the optimal deformable model: a discretization scheme by finite differences that generates an algorithm providing the approximating solution for energy-minimizing surfaces and a reconstruction method based on the Chebyshev discrete best approximation which approximates a plane deformable model represented by a finite set of points. Estimates for the approximation-error of these methods and results concerning their convergence or the topological structure of the set of unbounded divergence are presented, too.