Method for determination of root curvature radius using cone-beam computed tomography images

This article describes and discusses a method to determine root curvature radius by using cone-beam computed tomography (CBCT). The severity of root canal curvature is essential to select instrument and instrumentation technique. The diagnosis and planning of root canal treatment have traditionally been made based on periapical radiography. However, the higher accuracy of CBCT images to identify anatomic and pathologic alterations compared to panoramic and periapical radiographs has been shown to reduce the incidence of false-negative results. In high-resolution images, the measurement of root curvature radius can be obtained by circumcenter. Based on 3 mathematical points determined with the working tools of Planimp® software, it is possible to calculate root curvature radius in both apical and coronal directions. The CBCT-aided method for determination of root curvature radius presented in this article is easy to perform, reproducible and allows a more reliable and predictable endodontic planning, which reflects directly on a more efficacious preparation of curved root canals.

Diagnostic agreement between panoramic radiographs and color doppler images of carotid atheroma

The aim of this study was to investigate the agreement between diagnoses of calcified atheroma seen on panoramic radiographs and color Doppler images. Our interest stems from the fact that panoramic images can show the presence of atheroma regardless of the level of obstruction detected by color Doppler images. Panoramic and color Doppler images of 16 patients obtained from the archives of the Health Department of the city of Valença, RJ, Brazil, were analyzed in this study. Both sides of each patient were observed on the images, with a total of 32 analyzed cervical regions. The level of agreement between diagnoses was analyzed using the Kappa statistics. There was a high level of agreement, with a Kappa value of 0.78. In conclusion, panoramic radiographs can help detecting calcifications in the cervical region of patients susceptible to vascular diseases predisposing to myocardial infarction and cerebrovascular accidents. If properly trained and informed, dentists can refer their patients to a physician for a cardiovascular evaluation in order to receive proper and timely medical treatment.

Effect of insertion method on knoop hardness of high viscous glass ionomer cements

The aim of this study was to assess the Knoop hardness of three high viscous glass ionomer cements: G1 - Ketac Molar; G2 - Ketac Molar Easymix (3M ESPE) and G3 - Magic Glass ART (Vigodent). As a parallel goal, three different methods for insertion of Ketac Molar Easymix were tested: G4 - conventional spatula; G5 - commercial syringe (Centrix) and G6 - low-cost syringe. Ten specimens of each group were prepared and the Knoop hardness was determined 5 times on each specimen with a HM-124 hardness machine (25 g/30 s dwell time) after 24 h, 1 and 2 weeks. During the entire test period, the specimens were stored in liquid paraffin at 37ºC. Significant differences were found between G3 and G1/G2 (two-way ANOVA and Tukey's post hoc test; p<0.01). There was no significant difference in the results among the multiple ways of insertion. The glass ionomer cement Magic Glass ART showed the lowest hardness, while the insertion technique had no significant influence on hardness.

Computational adjustment technique for digital mammographic images based on the digitizer characteristic curve

We evaluated the performance of a novel procedure for segmenting mammograms and detecting clustered microcalcifications in two types of image sets obtained from digitization of mammograms using either a laser scanner, or a conventional ""optical"" scanner. Specific regions forming the digital mammograms were identified and selected, in which clustered microcalcifications appeared or not. A remarkable increase in image intensity was noticed in the images from the optical scanner compared with the original mammograms. A procedure based on a polynomial correction was developed to compensate the changes in the characteristic curves from the scanners, relative to the curves from the films. The processing scheme was applied to both sets, before and after the polynomial correction. The results indicated clearly the influence of the mammogram digitization on the performance of processing schemes intended to detect microcalcifications. The image processing techniques applied to mammograms digitized by both scanners, without the polynomial intensity correction, resulted in a better sensibility in detecting microcalcifications in the images from the laser scanner. However, when the polynomial correction was applied to the images from the optical scanner, no differences in performance were observed for both types of images. (C) 2008 SPIE and IS&T [DOI: 10.1117/1.3013544]

The Use of Latent Semantic Indexing to Mitigate OCR Effects of Related Document Images

Due to both the widespread and multipurpose use of document images and the current availability of a high number of document images repositories, robust information retrieval mechanisms and systems have been increasingly demanded. This paper presents an approach to support the automatic generation of relationships among document images by exploiting Latent Semantic Indexing (LSI) and Optical Character Recognition (OCR). We developed the LinkDI (Linking of Document Images) service, which extracts and indexes document images content, computes its latent semantics, and defines relationships among images as hyperlinks. LinkDI was experimented with document images repositories, and its performance was evaluated by comparing the quality of the relationships created among textual documents as well as among their respective document images. Considering those same document images, we ran further experiments in order to compare the performance of LinkDI when it exploits or not the LSI technique. Experimental results showed that LSI can mitigate the effects of usual OCR misrecognition, which reinforces the feasibility of LinkDI relating OCR output with high degradation.

Fluorescence images combined to statistic test for fingerprinting of citrus plants after bacterial infection

The citrus greening (or huanglongbing) disease has caused serious problems in citrus crops around the world. An early diagnostic method to detect this malady is needed due to the rapid dissemination of Candidatus Liberibacter asiaticus (CLas) in the field. This analytical study investigated the fluorescence responses of leaves from healthy citrus plants and those inoculated with CLas by images from a stereomicroscope and also evaluated their potential for the early diagnosis of the infection caused by this bacterium. The plants were measured monthly, and the evolution of the bacteria on inoculated plants was monitored by real-time quantitative polymerase chain reaction (RT-qPCR) amplification of CLas sequences. A statistical method was used to analyse the data. The selection of variables from histograms of colours (colourgrams) of the images was optimized using a paired Student's t-test. The intensity of counts for green colours from images of fluorescence had clearly minor variations for healthy plants than diseased ones. The darker green colours were the indicators of healthy plants and the light colours for the diseased. The method of fluorescence images is novel for fingerprinting healthy and diseased plants and provides an alternative to the current method represented by PCR and visual inspection. A new, non-subjective pattern of analysis and a non-destructive method has been introduced that can minimize the time and costs of analyses.

Determination of Three-Dimensional Left Ventricle Motion to Analyze Ventricular Dyssyncrony in SPECT Images

A method to compute three-dimension (3D) left ventricle (LV) motion and its color coded visualization scheme for the qualitative analysis in SPECT images is proposed. It is used to investigate some aspects of Cardiac Resynchronization Therapy (CRT). The method was applied to 3D gated-SPECT images sets from normal subjects and patients with severe Idiopathic Heart Failure, before and after CRT. Color coded visualization maps representing the LV regional motion showed significant difference between patients and normal subjects. Moreover, they indicated a difference between the two groups. Numerical results of regional mean values representing the intensity and direction of movement in radial direction are presented. A difference of one order of magnitude in the intensity of the movement on patients in relation to the normal subjects was observed. Quantitative and qualitative parameters gave good indications of potential application of the technique to diagnosis and follow up of patients submitted to CRT.

MEMORY TRAINING FOR OLDER ADULTS WITH LOW EDUCATION: MENTAL IMAGES VERSUS CATEGORIZATION

This study aimed to describe the benefits of memory training for older adults with low education. Twenty-nine healthy older adults with zero to two years of formal education participated. Sixteen participants received training based on categorization (categorization group = CATG) and 13 received training based on mental images (imagery group = IMG). One group served as control for the other because they trained with different strategies. Training was offered in eight sessions of 90 minutes. The participants were evaluated pre- and posttraining. IMG improved performance in episodic memory tests and had reduced depressive symptoms. CATG increased the use of categorization but did not increase performance in episodic memory tests. Results suggest that the strategy based on the creation of mental images was more effective for older adults with low formal education.

Images of a `good nurse` presented by teaching staff

Nursing is at the same time a vocation, a profession and a job. By nature, nursing is a moral endeavor, and being a `good nurse` is an issue and an aspiration for professionals. The aim of our qualitative research project carried out with 18 nurse teachers at a university nursing school in Brazil was to identify the ethical image of nursing. In semistructured interviews the participants were asked to choose one of several pictures, to justify their choice and explain what they meant by an ethical nurse. Five different perspectives were revealed: good nurses fulfill their duties correctly; they are proactive patient advocates; they are prepared and available to welcome others as persons; they are talented, competent, and carry out professional duties excellently; and they combine authority with power sharing in patient care. The results point to a transition phase from a historical introjection of religious values of obedience and service to a new sense of a secular, proactive, scientific and professional identity.

Online Mammographic Images Database for Development and Comparison of CAD Schemes

Considering the difficulties in finding good-quality images for the development and test of computer-aided diagnosis (CAD), this paper presents a public online mammographic images database free for all interested viewers and aimed to help develop and evaluate CAD schemes. The digitalization of the mammographic images is made with suitable contrast and spatial resolution for processing purposes. The broad recuperation system allows the user to search for different images, exams, or patient characteristics. Comparison with other databases currently available has shown that the presented database has a sufficient number of images, is of high quality, and is the only one to include a functional search system.

Ciratefi: An RST-invariant template matching with extension to color images

Template matching is a technique widely used for finding patterns in digital images. A good template matching should be able to detect template instances that have undergone geometric transformations. In this paper, we proposed a grayscale template matching algorithm named Ciratefi, invariant to rotation, scale, translation, brightness and contrast and its extension to color images. We introduce CSSIM (color structural similarity) for comparing the similarity of two color image patches and use it in our algorithm. We also describe a scheme to determine automatically the appropriate parameters of our algorithm and use pyramidal structure to improve the scale invariance. We conducted several experiments to compare grayscale and color Ciratefis with SIFT, C-color-SIFT and EasyMatch algorithms in many different situations. The results attest that grayscale and color Ciratefis are more accurate than the compared algorithms and that color-Ciratefi outperforms grayscale Ciratefi most of the time. However, Ciratefi is slower than the other algorithms.

AUTOMATIC CORONARY WALL SEGMENTATION IN INTRAVASCULAR ULTRASOUND IMAGES USING BINARY MORPHOLOGICAL RECONSTRUCTION

Intravascular ultrasound (IVUS) image segmentation can provide more detailed vessel and plaque information, resulting in better diagnostics, evaluation and therapy planning. A novel automatic segmentation proposal is described herein; the method relies on a binary morphological object reconstruction to segment the coronary wall in IVUS images. First, a preprocessing followed by a feature extraction block are performed, allowing for the desired information to be extracted. Afterward, binary versions of the desired objects are reconstructed, and their contours are extracted to segment the image. The effectiveness is demonstrated by segmenting 1300 images, in which the outcomes had a strong correlation to their corresponding gold standard. Moreover, the results were also corroborated statistically by having as high as 92.72% and 91.9% of true positive area fraction for the lumen and media adventitia border, respectively. In addition, this approach can be adapted easily and applied to other related modalities, such as intravascular optical coherence tomography and intravascular magnetic resonance imaging. (E-mail: matheuscardosomg@hotmail.com) (C) 2011 World Federation for Ultrasound in Medicine & Biology.

Providing Integrity and Authenticity in DICOM Images: A Novel Approach

The increasing adoption of information systems in healthcare has led to a scenario where patient information security is more and more being regarded as a critical issue. Allowing patient information to be in jeopardy may lead to irreparable damage, physically, morally, and socially to the patient, potentially shaking the credibility of the healthcare institution. Medical images play a crucial role in such context, given their importance in diagnosis, treatment, and research. Therefore, it is vital to take measures in order to prevent tampering and determine their provenance. This demands adoption of security mechanisms to assure information integrity and authenticity. There are a number of works done in this field, based on two major approaches: use of metadata and use of watermarking. However, there still are limitations for both approaches that must be properly addressed. This paper presents a new method using cryptographic means to improve trustworthiness of medical images, providing a stronger link between the image and the information on its integrity and authenticity, without compromising image quality to the end user. Use of Digital Imaging and Communications in Medicine structures is also an advantage for ease of development and deployment.

Recognition of noisy images by PLL networks

We use networks composed of three phase-locked loops (PLLs), where one of them is the master, for recognizing noisy images. The values of the coupling weights among the PLLs control the noise level which does not affect the successful identification of the input image. Analytical results and numerical tests are presented concerning the scheme performance. (c) 2008 Elsevier B.V. All rights reserved.