Volumetric texture description and discriminant feature selection for MRI

This paper considers the problem of classification of Magnetic Resonance Images using 2D and 3D texture measures. Joint statistics such as co-occurrence matrices are common for analysing texture in 2D since they are simple and effective to implement. However, the computational complexity can be prohibitive especially in 3D. In this work, we develop a texture classification strategy by a sub-band filtering technique that can be extended to 3D. We further propose a feature selection technique based on the Bhattacharyya distance measure that reduces the number of features required for the classification by selecting a set of discriminant features conditioned on a set training texture samples. We describe and illustrate the methodology by quantitatively analysing a series of images: 2D synthetic phantom, 2D natural textures, and MRI of human knees

Source identification for mobile devices, based on wavelet transforms combined with sensor imperfections

One of the most relevant applications of digital image forensics is to accurately identify the device used for taking a given set of images, a problem called source identification. This paper studies recent developments in the field and proposes the mixture of two techniques (Sensor Imperfections and Wavelet Transforms) to get better source identification of images generated with mobile devices. Our results show that Sensor Imperfections and Wavelet Transforms can jointly serve as good forensic features to help trace the source camera of images produced by mobile phones. Furthermore, the model proposed here can also determine with high precision both the brand and model of the device

A comparison of the Accuracy of Ultrasound and Computed Tomography in common diagnoses causing acute abdominal pain

Head-to-head comparison of ultrasound and CT accuracy in common diagnoses causing acute abdominal pain. Consecutive patients with abdominal pain for > 2 h and <5 days referred for imaging underwent both US and CT by different radiologists/radiological residents. An expert panel assigned a final diagnosis. Ultrasound and CT sensitivity and predictive values were calculated for frequent final diagnoses. Effect of patient characteristics and observer experience on ultrasound sensitivity was studied. Frequent final diagnoses in the 1,021 patients (mean age 47; 55% female) were appendicitis (284; 28%), diverticulitis (118; 12%) and cholecystitis (52; 5%). The sensitivity of CT in detecting appendicitis and diverticulitis was significantly higher than that of ultrasound: 94% versus 76% (p <0.01) and 81% versus 61% (p = 0.048), respectively. For cholecystitis, the sensitivity of both was 73% (p = 1.00). Positive predictive values did not differ significantly between ultrasound and CT for these conditions. Ultrasound sensitivity in detecting appendicitis and diverticulitis was not significantly negatively affected by patient characteristics or reader experience. CT misses fewer cases than ultrasound, but both ultrasound and CT can reliably detect common diagnoses causing acute abdominal pain. Ultrasound sensitivity was largely not influenced by patient characteristics and reader experience

Spatial Statistics of Visual Keypoints for Texture Recognition

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Long-term cardiac follow-up of athletes infected with SARS-CoV-2 after resumption of elite-level sports

OBJECTIVE: Longitudinal consequences and potential interactions of COVID-19 and elite-level sports and exercise are unclear. Therefore, we determined the long-term detrimental cardiac effects of the interaction between SARS-CoV-2 infection and the highest level of sports and exercise.METHODS: This prospective controlled study included elite athletes from the Evaluation of Lifetime participation in Intensive Top-level sports and Exercise cohort. Athletes infected with SARS-CoV-2were offered structured, additional cardiovascular screenings, including cardiovascular MRI (CMR). We compared ventricular volumes and function, late gadolinium enhancement (LGE) and T1 relaxation times, between infected and non-infected elite athletes, and collected follow-up data on cardiac adverse events, ventricular arrhythmia burden and the cessation of sports careers.RESULTS: We included 259 elite athletes (mean age 26±5 years; 40% women), of whom 123 were infected (9% cardiovascular symptoms) and 136 were controls. We found no differences in function and volumetric CMR parameters. Four infected athletes (3%) demonstrated LGE (one reversible), compared with none of the controls. During the 26.7 (±5.8) months follow-up, all four athletes resumed elite-level sports, without an increase in ventricular arrhythmias or adverse cardiac remodelling. None of the infected athletes reported new cardiac symptoms or events. The majority (n=118; 96%) still participated in elite-level sports; no sports careers were terminated due to SARS-CoV-2.CONCLUSIONS: This prospective study demonstrates the safety of resuming elite-level sports after SARS-CoV-2 infection. The medium-term risks associated with SARS-CoV-2 infection and elite-level sports appear low, as the resumption of elite sports did not lead to detrimental cardiac effects or increases in clinical events, even in the four elite athletes with SARS-CoV-2 associated myocardial involvement.</p

Rotation Invariant Texture Classification Using Binary Filter Response Pattern (BFRP)

13th International Conference on Computer Analysis of Images and Patterns, CAIP 2009, Munster, 2-4 September 2009Using statistical textons for texture classification has shown great success recently. The maximal response 8 (MR8) method, which extracts an 8-dimensional feature set from 38 filters, is one of state-of-the-art rotation invariant texture classification methods. However, this method has two limitations. First, it require a training stage to build a texton library, thus the accuracy depends on the training samples; second, during classification, each 8-dimensional feature is assigned to a texton by searching for the nearest texton in the library, which is time consuming especially when the library size is big. In this paper, we propose a novel texton feature, namely Binary Filter Response Pattern (BFRP). It can well address the above two issues by encoding the filter response directly into binary representation. The experimental results on the CUReT database show that the proposed BFRP method achieves better classification result than MR8, especially when the training dataset is limited and less comprehensive.Department of ComputingRefereed conference pape

A feature extraction software tool for agricultural object-based image analysis

A software application for automatic descriptive feature extraction from image-objects, FETEX 2.0, is presented and described in this paper. The input data include a multispectral high resolution digital image and a vector file in shapefile format containing the polygons or objects, usually extracted from a geospatial database. The design of the available descriptive features or attributes has been mainly focused on the description of agricultural parcels, providing a variety of information: spectral information from the different image bands; textural descriptors of the distribution of the intensity values based on the grey level co-occurrence matrix, the wavelet transform and a factor of edgeness; structural features describing the spatial arrangement of the elements inside the objects, based on the semivariogram curve and the Hough transform; and several descriptors of the object shape. The output file is a table that can be produced in four alternative formats, containing a vector of features for every object processed. This table of numeric values describing the objects from different points of view can be externally used as input data for any classification software. Additionally, several types of graphs and images describing the feature extraction procedure are produced, useful for interpretation and understanding the process. A test of the processing times is included, as well as an application of the program in a real parcel-based classification problem, providing some results and analyzing the applicability, the future improvement of the methodologies, and the use of additional types of data sets. This software is intended to be a dynamic tool, integrating further data and feature extraction algorithms for the progressive improvement of land use/land cover database classification and agricultural database updating processes. © 2011 Elsevier B.V.The authors appreciate the financial support provided by the Spanish Ministerio de Ciencia e Innovacion and the FEDER in the framework of the Project CGL2009-14220 and CGL2010-19591/BTE, the Spanish Institut Geografico Nacional (IGN), Institut Cartografico Valenciano (ICV), Institut Murciano de Investigacion y Desarrollo Agrario y Alimentario (IMIDA) and Banco de Terras de Galicia (Bantegal).Ruiz Fernández, LÁ.; Recio Recio, JA.; Fernández-Sarría, A.; Hermosilla, T. (2011). A feature extraction software tool for agricultural object-based image analysis. Computers and Electronics in Agriculture. 76(2):284-296. https://doi.org/10.1016/j.compag.2011.02.007S28429676

Contemporary review of risk-stratified management in acute uncomplicated and complicated diverticulitis

BACKGROUND: Acute colonic diverticulitis is a common clinical condition. Severity of the disease is based on clinical, laboratory, and radiological investigations and dictates the need for medical or surgical intervention. Recent clinical trials have improved the understanding of the natural history of the disease resulting in new approaches to and better evidence for the management of acute diverticulitis. METHODS: We searched the Cochrane Library (years 2004-2015), MEDLINE (years 2004-2015), and EMBASE (years 2004-2015) databases. We used the search terms "diverticulitis, colonic" or "acute diverticulitis" or "divertic*" in combination with the terms "management," "antibiotics," "non-operative," or "surgery." Registers for clinical trials (such as the WHO registry and the https://clinicaltrials.gov/) were searched for ongoing, recruiting, or closed trials not yet published. RESULTS: Antibiotic treatment can be avoided in simple, non-complicated diverticulitis and outpatient management is safe. The management of complicated disease, ranging from a localized abscess to perforation with diffuse peritonitis, has changed towards either percutaneous or minimally invasive approaches in selected cases. The role of laparoscopic lavage without resection in perforated non-fecal diverticulitis is still debated; however, recent evidence from two randomised controlled trials has found a higher re-intervention in this group of patients. CONCLUSIONS: A shift in management has occurred towards conservative management in acute uncomplicated disease. Those with uncomplicated acute diverticulitis may be treated without antibiotics. For complicated diverticulitis with purulent peritonitis, the use of peritoneal lavage appears to be non-superior to resection