Search results for "Image Interpretation"
showing 10 items of 201 documents
Automatic detection and quantification of ground-glass opacities on high-resolution CT using multiple neural networks: comparison with a density mask.
2000
We compared multiple neural networks with a density mask for the automatic detection and quantification of ground-glass opacities on high-resolution CT under clinical conditions.Eighty-four patients (54 men and 30 women; age range, 18-82 years; mean age, 49 years) with a total of 99 consecutive high-resolution CT scans were enrolled in the study. The neural network was designed to detect ground-glass opacities with high sensitivity and to omit air-tissue interfaces to increase specificity. The results of the neural network were compared with those of a density mask (thresholds, -750/-300 H), with a radiologist serving as the gold standard.The neural network classified 6% of the total lung a…
Assessment of atrial diastolic function in patients with hypertrophic cardiomyopathy by cine magnetic resonance imaging
2015
Purpose: This study was conducted to assess the role of atrial function by cardiac magnetic resonance (CMR) for the evaluation of diastolic physiology in patients with hypertrophic cardiomyopathy (HCM) compared to healthy controls. Materials and methods: We enrolled 23 consecutive patients affected by HCM and 43 healthy subjects as age-matched control cases (CC). CMR was performed through acquisition of cine steady-state free precession sequences using a 1.5-T scanner. Image postprocessing was carried out using Tracking Tool software. Results: Atrial volumes were significantly higher in patients with HCM compared to CC: maximum atrial volume (p = 0.007) and minimum atrial volume (p = 0.01).…
Cingulo-Insular Structural Alterations Associated with Psychogenic Symptoms, Childhood Abuse and PTSD in Functional Neurological Disorders
2017
Objective Adverse early-life events are predisposing factors for functional neurological disorder (FND) and post-traumatic stress disorder (PTSD). Cingulo-insular regions are implicated in the biology of both conditions and are sites of stress-mediated neuroplasticity. We hypothesised that functional neurological symptoms and the magnitude of childhood abuse would be associated with overlapping anterior cingulate cortex (ACC) and insular volumetric reductions, and that FND and PTSD symptoms would map onto distinct cingulo-insular areas. Methods This within-group voxel-based morphometry study probes volumetric associations with self-report measures of functional neurological symptoms, advers…
Plantar fascia evaluation with a dedicated magnetic resonance scanner in weight-bearing position: our experience in patients with plantar fasciitis a…
2010
Purpose. This study assessed the usefulness of upright weight-bearing examination of the ankle/hind foot performed with a dedicated magnetic resonance (MR)imaging scanner in the evaluation of the plantar fascia in healthy volunteers and in patients with clinical evidence of plantar fasciitis. Materials and methods. Between January and March 2009, 20 patients with clinical evidence of plantar fasciitis (group A) and a similar number of healthy volunteers (group B) underwent MR imaging of the ankle/hind foot in the upright weight-bearing and conventional supine position. A 0.25-Tesla MR scanner (G-Scan, Esaote SpA, Genoa, Italy) was used with a dedicated receiving coil for the ankle/hind foot…
Standardized T2* map of normal human heart in vivo to correct T2* segmental artefacts.
2007
A segmental, multislice, multi-echo T2* MRI approach could be useful in heart iron-overloaded patients to account for heterogeneous iron distribution, demonstrated by histological studies. However, segmental T2* assessment in heart can be affected by the presence of geometrical and susceptibility artefacts, which can act on different segments in different ways. The aim of this study was to assess T2* value distribution in the left ventricle and to develop a correction procedure to compensate for artefactual variations in segmental analysis. MRI was performed in four groups of 22 subjects each: healthy subjects (I), controls (II) (thalassemia intermedia patients without iron overload), thala…
Validation of tumour-free distance as novel prognostic marker in early-stage cervical cancer: a retrospective, single-centre, cohort study
2021
Background: The aim of the present study was to assess the prognostic value of tumour-free distance (TFD), defined as the minimum distance of uninvolved stroma between the tumour and peri-cervical stromal ring, in early-stage cervical cancer. Methods: Patients with pathologic FIGO 2009 stage IA1–IIA2 cervical cancer, treated by primary radical surgical treatment between 01/2000 and 11/2019, were retrospectively included. Adjuvant treatment was administered according to the presence of previously established pathologic risk factors. TFD was measured histologically on the hysterectomy specimen. Pre-operative TFD measured at MRI-scan from a cohort of patients was reviewed and compared with pat…
Reference Ranges and Distribution of Placental Volume by 3-Dimensional Virtual Organ Computer-Aided Analysis Between 11 Weeks and 13 Weeks 6 Days
2013
OBJECTIVES The purpose of this study was to determine the feasibility, reproducibility, and distribution of placental volume measurements according to the crown-rump length between 11 weeks and 13 weeks 6 days. METHODS Images were acquired in 128 pregnancies followed in Burgundy during first-trimester screening sonography using an abdominal 3-dimensional transducer. The placental volume was then calculated by the virtual organ computer-aided analysis method with a rotation angle of 30° by a single operator. RESULTS Placental volumes ranged from 33.3 to 107.6 cm(3) with a mean ± SD of 62.3 ± 14.8 cm(3); the 5th and 10th percentiles were 38.0 and 44.20 cm(3), respectively, whereas the 90th an…
Quantifying stenosis in renal arteriograms: a fuzzy syntactic analysis.
1999
AbstractThe introduction of fuzzy logic improves a system for the automatic quantification of renal artery lesions seen in digital subtraction angiograms. A two-step approach has been followed. An earlier system based on non-fuzzy syntactic analysis provided a clear symbolic description of the stenotic lesions. Although this system worked correctly, it did not take into account the variability and uncertainty inherent to image processing and to knowledge on the reference diameter. This system has been improved by the introduction of fuzzy logic in the representation of the reference diameter. It provides a description of the stenosis in terms of fuzzy quantities. To illustrate the benefits …
Computer Modeling for the Prediction of Thoracic Aortic Stent Graft Collapse
2011
OBJECTIVE: To assess the biomechanical implications of excessive stent protrusion into the aortic arch in relation to thoracic aortic stent graft (TASG) collapse by simulating the structural load and quantifying the fluid dynamics on the TASG wall protrusion extended into a model arch. METHODS: One-way coupled fluid-solid interaction analyses were performed to investigate the flow-induced hemodynamic and structural loads exerted on the proximal protrusion of the TASG and aortic wall reconstructed from a patient who underwent traumatic thoracic aortic injury repair. Mechanical properties of a Gore TAG thoracic endoprosthesis (W. L. Gore and Assoc, Flagstaff, Ariz) were assessed via experimen…
LogDet divergence-based metric learning with triplet constraints and its applications.
2014
How to select and weigh features has always been a difficult problem in many image processing and pattern recognition applications. A data-dependent distance measure can address this problem to a certain extent, and therefore an accurate and efficient metric learning becomes necessary. In this paper, we propose a LogDet divergence-based metric learning with triplet constraints (LDMLT) approach, which can learn Mahalanobis distance metric accurately and efficiently. First of all, we demonstrate the good properties of triplet constraints and apply it in LogDet divergence-based metric learning model. Then, to deal with high-dimensional data, we apply a compressed representation method to learn…