Quantification of temporomandibular joint space in patients with juvenile idiopathic arthritis assessed by cone beam computerized tomography.

Objective: To describe a method to calculate the total intra-articular volume (inter-osseous space) of the temporomandibular joint (TMJ) determined by cone-beam computed tomography (CBCT). This could be used as a marker of tissue proliferation and different degrees of soft tissue hyperplasia in juvenile idiopathic arthritis (JIA) patients.

Materials And Methods: Axial single-slice CBCT images of cross-sections of the TMJs of 11 JIA patients and 11 controls were employed.

TMJ contrast enhancement in CBCT images using a new algorithm.

Magnetic resonance imaging (MRI) is considered the gold standard to reliably diagnose inflammation in the temporomandibular joint (TMJ) of patients with juvenile idiopathic arthritis (JIA). However, even MRI imaging is dependent on the familiarity of the radiologist with the normal appearance of the TMJ; therefore, new approaches are needed. Our purpose here is to improve imaging quality of cone beam computed tomography (CBCT) as a tool to help in the diagnosis of JIA in the TMJ.

AutoMeKin2021: An open-source program for automated reaction discovery.

AutoMeKin2021 is an updated version of tsscds2018, a program for the automated discovery of reaction mechanisms (J. Comput. Chem.

Deep learning method for aortic root detection.

Background: Computed tomography angiography (CTA) is a preferred imaging technique for a wide range of vascular diseases. However, extensive manual analysis is required to detect and identify several anatomical landmarks for clinical application. This study demonstrates the feasibility of a fully automatic method for detecting the aortic root, which is a key anatomical landmark in this type of procedure.

Automatic detection of anatomical landmarks of the aorta in CTA images.

Computed tomography angiography (CTA) is one of the most common vascular imaging modalities. However, for clinical use, it still requires laborious manual analysis. This study demonstrates the feasibility of a fully automated technology for the accurate detection and identification of several anatomical reference points (landmarks), commonly used in intravascular imaging.

Noble microfluidic system for bioceramic nanoparticles engineering.

Bioceramic nanoparticles have many potential applications within the biomedical device industry. However, these applications demand a precise control of their sizes, shapes and morphology which play a main role in most properties. In this work, we report a new route for the synthesis of hydroxyapatite nanoparticles using a microfluidic device.

Automatic estimation of the aortic lumen geometry by ellipse tracking.

Purpose: The shape and size of the aortic lumen can be associated with several aortic diseases. Automated computer segmentation can provide a mechanism for extracting the main features of the aorta that may be used as a diagnostic aid for physicians. This article presents a new fully automated algorithm to extract the aorta geometry for either normal (with and without contrast) or abnormal computed tomography (CT) cases.

Bootstrap-based procedures for inference in nonparametric receiver-operating characteristic curve regression analysis.

Prior to using a diagnostic test in a routine clinical setting, the rigorous evaluation of its diagnostic accuracy is essential. The receiver-operating characteristic curve is the measure of accuracy most widely used for continuous diagnostic tests. However, the possible impact of extra information about the patient (or even the environment) on diagnostic accuracy also needs to be assessed.

Automatic characterization of thoracic aortic aneurysms from CT images.

Accurate determination of the diameter is an important step for diagnosis and follow-up of aortic abnormalities such as aneurysms, caused by dilation of the vessel lumen. In this work we focus on the development of an automatic method for measuring the calibre of the thoracic aorta. The method is based on the application of principal component analysis on normal planes extracted from the aorta to establish the main axis of each section of the vessel.

A hybrid method based on level set and 3D region growing for segmentation of the thoracic aorta.

This study sought to develop a completely automatic method for image segmentation of the thoracic aorta. We used a total of 4682 images from 10 consecutive patients. The proposed method is based on the use of level set and region growing, automatically initialized using the Hough transform.

Quantification of Right and Left Ventricular Function in Cardiac MR Imaging: Comparison of Semiautomatic and Manual Segmentation Algorithms.

The purpose of this study was to evaluate the performance of a semiautomatic segmentation method for the anatomical and functional assessment of both ventricles from cardiac cine magnetic resonance (MR) examinations, reducing user interaction to a "mouse-click". Fifty-two patients with cardiovascular diseases were examined using a 1.5-T MR imaging unit.

Application of the iris filter for automatic detection of pulmonary nodules on computed tomography images.

We have developed a computer-aided diagnosis (CAD) system to detect pulmonary nodules on thin-slice helical computed tomography (CT) images. We have also investigated the capability of an iris filter to discriminate between nodules and false-positive findings. Suspicious regions were characterized with features based on the iris filter output, gray level and morphological features, extracted from the CT images.

Selecting variables in non-parametric regression models for binary response. An application to the computerized detection of breast cancer.

In many biomedical applications, interest lies in being able to distinguish between two possible states of a given response variable, depending on the values of certain continuous predictors. If the number of predictors, p, is high, or if there is redundancy among them, it then becomes important to decide on the selection of the best subset of predictors that will be able to obtain the models with greatest discrimination capacity. With this aim in mind, logistic generalized additive models were considered and receiver operating characteristic (ROC) curves were applied in order to determine and compare the discriminatory capacity of such models.

Categorical variables, interactions and generalized additive models. Applications in computer-aided diagnosis systems.

Recently, the generalized additive models (GAMs) have been presented as a novel statistical approach to distinguish lesion/non-lesion in computer-aided diagnosis (CAD) systems. In this paper, we present an extension of the GAM that allows for the introduction of factors and their interactions with continuous variables, for reducing false positives in a CAD system for detecting clustered microcalcifications in digital mammograms. The results obtained have shown an increase in the sensitivity from 83.

A new general-purpose fully automatic baseline-correction procedure for 1D and 2D NMR data.

A new procedure for automatic baseline correction of NMR data sets is presented. It is based on an improved automatic recognition of signal-free regions that uses a Continuous Wavelet transform derivative calculation, followed by a baseline modelling procedure based on the Whittaker smoother algorithm. The method has been proven to automatically flatten 1D and 2D NMR spectra with large baseline distortions arising from different sources, is tolerant to low signal-to-noise ratio spectra, and to signals of varying widths in a single spectrum.

Computerized detection of breast masses in digitized mammograms.

We propose a system to detect malignant masses on mammograms. We investigated the behavior of an iris filter at different scales. After iris filter was applied, suspicious regions were segmented by means of an adaptive threshold.

Effects of JPEG2000 data compression on an automated system for detecting clustered microcalcifications in digital mammograms.

The functionalities of the JPEG2000 standard have led to its incorporation into digital imaging and communications in medicine (DICOM), which makes this compression method available for medical systems. In this study, we evaluated the compression of mammographic images with JPEG2000 (16 : 1, 20 : 1, 40 : 1, 60.4 : 1, 80: 1, and 106 : 1) for applications with a computer-aided detection (CAD) system for clusters of microcalcifications.

Using generalized additive models for construction of nonlinear classifiers in computer-aided diagnosis systems.

Several investigators have pointed out the possibility of using computer-aided diagnosis (CAD) schemes, as second readers, to help radiologists in the interpretation of images. One of the most important aspects to be considered when the diagnostic imaging systems are analyzed is the evaluation of their diagnostic performance. To perform this task, receiver operating characteristic curves are the method of choice.

Free-response receiver operating characteristic evaluation of lossy JPEG2000 and object-based set partitioning in hierarchical trees compression of digitized mammograms.

Purpose: To assess the effects of two irreversible wavelet-based compression algorithms--Joint Photographic Experts Group (JPEG) 2000 and object-based set partitioning in hierarchical trees (SPIHT)--on the detection of clusters of microcalcifications and masses on digitized mammograms.

Materials And Methods: The use of the images in this retrospective image-collection study was approved by the institutional review board, and patient informed consent was not required. One hundred twelve mammographic images (28 with one or two clusters of microcalcifications, 19 with one mass, 17 with both abnormal findings, and 48 with normal findings) obtained in 60 women who ranged in age from 25 to 79 years were digitized and compressed at 40:1 and 80:1 by using the JPEG2000 and object-based SPIHT methods.

Wavelet-based ultra-high compression of multidimensional NMR data sets.

The application of a lossy data compression algorithm based on wavelet transform to 2D NMR spectra is presented. We show that this algorithm affords rapid and extreme compression ratios (e.g.

A compression and transmission scheme of computer tomography images for telemedicine based on JPEG2000.

A newly developed lossy compression and transmission scheme valid for telemedicine is described. The system uses computed tomography (CT) images and is based on JPEG2000. Different compression rates were applied to different regions within the image.

Computer aided diagnosis for breast masses detection on a telemammography system.

A Computer-Aided Diagnosis (CAD) scheme for breast masses detection has been developed and integrated as a part of a telemammography system. This work derives from the close cooperation between the Laboratory for Radiologic Image Research of the University of Santiago de Compostela (Spain) and the company Intelsis Sistemas Inteligentes (Santiago de Compostela, Spain). This cooperation has been supported by funds from different projects, mainly from the European Union, the Spanish Health Administration, and the Galician Public Health's Service.

Region-based wavelet coding methods for digital mammography.

Spatial resolution and contrast sensitivity requirements for some types of medical image techniques, including mammography, delay the implementation of new digital technologies, namely, computer-aided diagnosis, picture archiving and communications systems, or teleradiology. In order to reduce transmission time and storage cost, an efficient data-compression scheme to reduce digital data without significant degradation of medical image quality is needed. In this study, we have applied two region-based compression methods to digital mammograms.

A high resolution workstation prototype for diagnosis of digital mammograms.

The development of a total digital high resolution mammography display system must meet a number of requirements that remain a challenge nowadays, most probably because of the special nature of breast imaging. In this paper, we discuss our particular approach to address some problems concerning the complexity of soft-copy diagnosis in digital mammography, such as image quality and user interface evaluation. Based on the experience obtained in the previous implementation of a medical image browser, a more ambitious project is being developed at the Department of Radiology of the University of Santiago de Compostela (Spain) in collaboration with the Department of Medical Informatics of INTELSIS, an emerging software company in our country.