Quantitative analysis of complex nanocomposites based on straight skeletonization

Bones are complex nanocomposites composed mainly by hydroxyapatite nanocrystals. Different factors characterize its morphology: composition, length, orientation, roughness. To increase our understanding of the tissue morphology at this fundamental lever of organization, a new method based on the straight skelonization of the images obtained by electronic microscopy is proposed. The method detects and measures the length and angularity of any straight edge of over the image. The technique resolved several test patterns independent of size and angle of rotation. Several samples obtained from different substrates were analyzed with the method. The results were consistent with those values obtained from conventional methods. Although still limited as a laboratory application, shape analysis has the potential to provide insight into the mechanisms of crystal growing and may provide a basis for specifications or guidelines for the manufacturing of biomaterial for bone tissue engineering. Our proposed automated computational method for the analysis and quantification digital images of bone tissue at microscale provide a rapid and accurate of the mechanical properties of the tissue.Fil: Tahoces, Pablo G.. Universidad de Santiago de Compostela; EspañaFil: Messina, Paula Verónica. Universidad Nacional del Sur; ArgentinaFil: Ruso, Juan Manuel. Universidad de Santiago de Compostela; Españ

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. From the top of the glenoid fossa, in the caudal direction, an average of 26 slices were defined in each joint (N = 44). The interosseous space was manually delimited from each slice by using dedicated software that includes a graphic interface. TMJ volumes were calculated by adding the areas measured in each slice. Two volumes were defined: Ve−i and Vi, where Ve−i is the inter-osseous space, volume defined by the borders of the fossa and Vi is the internal volume defined by the condyle. An intra-articular volume filling index (IF) was defined as Ve−i/Vi, which represents the filling of the space. Results The measured space of the intra-articular volume, corresponding to the intra-articular soft tissue and synovial fluid, was more than twice as large in the JIA group as in the control group. Conclusion The presented method, based on CBCT, is feasible for assessing inter-osseus joint volume of the TMJ and delimits a threshold of intra-articular changes related to intra-articular soft tissue proliferation, based on differences in volumes. Intra-articular soft tissue is found to be enlarged in JIA patientsS

Comparative study of ROC regression techniques--Applications for the computer-aided diagnostic system in breast cancer detection

The receiver operating characteristic (ROC) curve is the most widely used measure for statistically evaluating the discriminatory capacity of continuous biomarkers. It is well known that, in certain circumstances, the markers' discriminatory capacity can be affected by factors, and several ROC regression methodologies have been proposed to incorporate covariates in the ROC framework. An in-depth simulation study of different ROC regression models and their application in the emerging field of automatic detection of tumour masses is presented. In the simulation study different scenarios were considered and the models were compared to each other on the basis of the mean squared error criterion. The application of the reviewed ROC regression techniques in evaluating computer-aided diagnostic (CAD) schemes can become a major factor in the development of such systems in Radiology.ROC curve Regression techniques B-splines Computer-aided diagnosis

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. Several parameters of both ventricles, such as end-diastolic volume (EDV), end-systolic volume (ESV) and ejection fraction (EF), were quantified by an experienced operator using the conventional method based on manually-defined contours, as the standard of reference; and a novel semiautomatic segmentation method based on edge detection, iterative thresholding and region growing techniques, for evaluation purposes. No statistically significant differences were found between the two measurement values obtained for each parameter (p > 0.05). Correlation to estimate right ventricular function was good (r > 0.8) and turned out to be excellent (r > 0.9) for the left ventricle (LV). Bland-Altman plots revealed acceptable limits of agreement between the two methods (95%). Our study findings indicate that the proposed technique allows a fast and accurate assessment of both ventricles. However, further improvements are needed to equal results achieved for the right ventricle (RV) using the conventional methodology