Protecting medical images with biometric information

Medical images are private to doctor and patient. Digital medical images should be protected against unauthorized viewers. One way to protect digital medical images is using cryptography to encrypt the images. This paper proposes a method for encrypting medical images with a traditional symmetric cryptosystem. We use biometrics to protect the cryptographic key. Both encrypted image and cryptographic key can be transmitted over public networks with security and only the person that owns the biometrics information used in key protection can decrypt the medical image. © Springer Science+Business Media B.V. 2008.

Automatic segmentation of digital images applied in cardiac medical images

The digital image processing has been applied in several areas, especially where it is necessary use tools for feature extraction and to get patterns of the studied images. In an initial stage, the segmentation is used to separate the image in parts that represents a interest object, that may be used in a specific study. There are several methods that intends to perform such task, but is difficult to find a method that can easily adapt to different type of images, that often are very complex or specific. To resolve this problem, this project aims to presents a adaptable segmentation method, that can be applied to different type of images, providing an better segmentation. The proposed method is based in a model of automatic multilevel thresholding and considers techniques of group histogram quantization, analysis of the histogram slope percentage and calculation of maximum entropy to define the threshold. The technique was applied to segment the cell core and potential rejection of tissue in myocardial images of biopsies from cardiac transplant. The results are significant in comparison with those provided by one of the best known segmentation methods available in the literature. © 2010 IEEE.

A New Family of Distance Functions for Perceptual Similarity Retrieval of Medical Images

A long-standing challenge of content-based image retrieval (CBIR) systems is the definition of a suitable distance function to measure the similarity between images in an application context which complies with the human perception of similarity. In this paper, we present a new family of distance functions, called attribute concurrence influence distances (AID), which serve to retrieve images by similarity. These distances address an important aspect of the psychophysical notion of similarity in comparisons of images: the effect of concurrent variations in the values of different image attributes. The AID functions allow for comparisons of feature vectors by choosing one of two parameterized expressions: one targeting weak attribute concurrence influence and the other for strong concurrence influence. This paper presents the mathematical definition and implementation of the AID family for a two-dimensional feature space and its extension to any dimension. The composition of the AID family with L (p) distance family is considered to propose a procedure to determine the best distance for a specific application. Experimental results involving several sets of medical images demonstrate that, taking as reference the perception of the specialist in the field (radiologist), the AID functions perform better than the general distance functions commonly used in CBIR.

Evaluating craniofacial asymmetry with digital cephalometric images and cone-beam computed tomography

Introduction: The aim of this study was to evaluate craniofacial asymmetry by using 2-dimensional (2D) poster-oanterior cephalometric images, 3-dimensional cone-beam computed tomography (CBCT), and physical measurements (gold standard). Methods: Ten dry human skulls were assessed, and radiopaque markers were placed on 17 skeletal landmarks. Twenty linear measurements were taken on each side to compare the right and left sides and to compare these measurements with the physical measurements made with a digital caliper. To acquire the 2D posteroanterior radiographs, an Extraoral Phosphor Storage Plate (Air Techniques, Chicago, Ill) was used as the image receptor with a Eureka x-ray-Duocon Machlett unit (Machlett Laboratores, Chicago, Ill). Three-dimensional imaging data were acquired from a CB MercuRay (Hitachi Medical, Tokyo, Japan). Results: on average, the right side was larger than the left for most of the 20 distances evaluated in the digital 2D and the CBCT images, and there was poor agreement between the digital 2D images and the physical measurements (kappa = 0.0609) and almost perfect agreement (kappa = 0.92) between the CBCT and physical measurements when individual measurements were considered. Conclusions: Human skulls, with no apparent asymmetry, had some differences between the right and left sides, with dominance for the right side but with no clinical significance. CBCT can better evaluate craniofacial morphology when compared with digital 2D images. (Am J Orthod Dentofacial Orthop 2011; 139: e523-e531)

Geometric modeling from the medical images in the CAD system to support prosthesis design

This paper presents an individual designing prosthesis for surgical use and proposes a methodology for such design through mathematical extrapolation of data from digital images obtained via tomography of individual patient's bones. Individually tailored prosthesis designed to fit particular patient requirements as accurately as possible should result in more successful reconstruction, enable better planning before surgery and consequently fewer complications during surgery. Fast and accurate design and manufacture of personalized prosthesis for surgical use in bone replacement or reconstruction is potentially feasible through the application and integration of several different existing technologies, which are each at different stages of maturity. Initial case study experiments have been undertaken to validate the research concepts by making dimensional comparisons between a bone and a virtual model produced using the proposed methodology and a future research directions are discussed.

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]

Primary ciliary dyskinesia: evaluation using cilia beat frequency assessment via spectral analysis of digital microscopy images

Olm MA, Kogler JE Jr, Macchione M, Shoemark A, Saldiva PH, Rodrigues JC. Primary ciliary dyskinesia: evaluation using cilia beat frequency assessment via spectral analysis of digital microscopy images. J Appl Physiol 111: 295-302, 2011. First published May 5, 2011; doi:10.1152/japplphysiol.00629.2010.-Ciliary beat frequency (CBF) measurements provide valuable information for diagnosing of primary ciliary dyskinesia (PCD). We developed a system for measuring CBF, used it in association with electron microscopy to diagnose PCD, and then analyzed characteristics of PCD patients. 1 The CBF measurement system was based on power spectra measured through digital imaging. Twenty-four patients suspected of having PCD (age 1-19 yr) were selected from a group of 75 children and adolescents with pneumopathies of unknown causes. Ten healthy, nonsmoking volunteers (age >= 17 yr) served as a control group. Nasal brush samples were collected, and CBF and electron microscopy were performed. PCD was diagnosed in 12 patients: 5 had radial spoke defects, 3 showed absent central microtubule pairs with transposition, 2 had outer dynein arm defects, 1 had a shortened outer dynein arm, and 1 had a normal ultrastructure. Previous studies have reported that the most common cilia defects are in the dynein arm. As expected, the mean CBF was higher in the control group (P < 0.001) and patients with normal ultrastructure (P < 0.002), than in those diagnosed with cilia ultrastructural defects (i.e., PCD patients). An obstructive ventilatory pattern was observed in 70% of the PCD patients who underwent pulmonary function tests. All PCD patients presented bronchial wall thickening on chest computed tomography scans. The protocol and diagnostic techniques employed allowed us to diagnose PCD in 16% of patients in this study.

Reversible and high capacity data hiding in medical images

In this paper we introduce a highly efficient reversible data hiding system. It is based on dividing the image into tiles and shifting the histograms of each image tile between its minimum and maximum frequency. Data are then inserted at the pixel level with the largest frequency to maximize data hiding capacity. It exploits the special properties of medical images, where the histogram of their nonoverlapping image tiles mostly peak around some gray values and the rest of the spectrum is mainlyempty. The zeros (or minima) and peaks (maxima) of the histograms of the image tiles are then relocated to embed the data. The grey values of some pixels are therefore modified.High capacity, high fidelity, reversibility and multiple data insertions are the key requirements of data hiding in medical images. We show how histograms of image tiles of medical images can be exploited to achieve these requirements. Compared with data hiding method applied to the whole image, our scheme can result in 30%-200% capacity improvement and still with better image quality, depending on the medical image content. Additional advantages of the proposed method include hiding data in the regions of non-interest and better exploitation of spatial masking.

Compact Representations for Fast Nonrigid Registration of Medical Images

We develop efficient techniques for the non-rigid registration of medical images by using representations that adapt to the anatomy found in such images. Images of anatomical structures typically have uniform intensity interiors and smooth boundaries. We create methods to represent such regions compactly using tetrahedra. Unlike voxel-based representations, tetrahedra can accurately describe the expected smooth surfaces of medical objects. Furthermore, the interior of such objects can be represented using a small number of tetrahedra. Rather than describing a medical object using tens of thousands of voxels, our representations generally contain only a few thousand elements. Tetrahedra facilitate the creation of efficient non-rigid registration algorithms based on finite element methods (FEM). We create a fast, FEM-based method to non-rigidly register segmented anatomical structures from two subjects. Using our compact tetrahedral representations, this method generally requires less than one minute of processing time on a desktop PC. We also create a novel method for the non-rigid registration of gray scale images. To facilitate a fast method, we create a tetrahedral representation of a displacement field that automatically adapts to both the anatomy in an image and to the displacement field. The resulting algorithm has a computational cost that is dominated by the number of nodes in the mesh (about 10,000), rather than the number of voxels in an image (nearly 10,000,000). For many non-rigid registration problems, we can find a transformation from one image to another in five minutes. This speed is important as it allows use of the algorithm during surgery. We apply our algorithms to find correlations between the shape of anatomical structures and the presence of schizophrenia. We show that a study based on our representations outperforms studies based on other representations. We also use the results of our non-rigid registration algorithm as the basis of a segmentation algorithm. That algorithm also outperforms other methods in our tests, producing smoother segmentations and more accurately reproducing manual segmentations.

Pixel intensity and fractal analyses: detecting osteoporosis in perimenopausal and postmenopausal women by using digital panoramic images

Objective. Pixel intensity values (PI) and fractal dimensions (FD) were compared in selected mandibular regions on digital panoramic images of normal, osteopenic, and osteoporotic perimenopausal and postmenopausal women to evaluate their relative efficacies in detecting osteoporotic-associated bone density changes.Study design. Standardized mandibular angle, body, and canine/premolar (C/PM) regions on 54 charge-coupied device (CCD) digital panoramic images of normal and potentially osteoporotic postmenopausal women were analyzed for PI and FD. Lumbar spine and femoral neck dual-energy x-ray absorptiometry QXA) on each patient served as the reference standard examination. Pearson correlation coefficients and analysis of variance (ANOVA) were performed.Results. There was significant correlation among PI measurements (P < 0.01), and no significant correlation between FD. C/PM had significantly lower PI than control C/PM (P = 0.049).Conclusions. Osteoporotic changes in mandibular C/PM cancellous bone were detected in our study population on CCD digital panoramic images by using a robust image analysis paradigm. Future automated application of such image analysis could enable widespread, cost effective screening for osteoporosis in dental settings.

Recursive hierarchic segmentation analysis of bone mineral density changes on digital panoramic images

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Development of a simple method for determination of NO2 in air using digital scanner images

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Output only based modal analysis of a reduced scale building using digital camera images

The article discusses a proposal of displacement measurement using a unique digital camera aiming at to exploit its feasibility for Modal Analysis applications. The proposal discusses a non-contact measuring approach able to measure multiple points simultaneously by using a unique digital camera. A modal analysis of a reduced scale lab building structure based only at the responses of the structure measured with the camera is presented. It focuses at the feasibility of using a simple ordinary camera for performing the output only modal analysis of structures and its advantage. The modal parameters of the structure are estimated from the camera data and also by using ordinary experimental modal analysis based on the Frequency Response Function (FRF) obtained by using the usual sensors like accelerometer and force cell. The comparison of the both analysis showed that the technique is promising noncontact measuring tool relatively simple and effective to be used in structural modal analysis