Enhanced detection in CT colonography using adaptive diffusion filtering

Computer-aided detection (CAD) is a computerized procedure in medical science that supports the medical team’s interpretations and decisions. CAD uses information from a medical imaging modality such as Computed Tomography to detect suspicious lesions. Algorithms to detect these lesions are based on geometrical models which can describe the local structures and thus provide potential region candidates. Geometrical descriptive models are very dependent on the data quality which may affect the false positive rates in CAD. In this paper we propose an efficient adaptive diffusion technique that adaptively controls the diffusion flux of the local structures in the data using robust statistics. The proposed method acts isotropically in the homogeneous regions and anisotropically in the vicinity of jump discontinuities. This method structurally enhances the data and makes the geometrical descriptive models robust. For the iterative solver, we use an efficient gradient descent flows solver based on a PDE formulation of the problem. The whole proposed strategy, which makes use of adaptive diffusion filter coupled with gradient descent flows has been developed and evaluated on clinical data in the application to colonic polyp detection in Computed Tomography Colonoscopy

An unconstrained binary quadratic programming for the maximum independent set problem

For a given graph G = (V, E) the maximum independent set problem is to find the largest subset of pairwise nonadjacent vertices. We propose a new model which is a reformulation of the maximum independent set problem as an unconstrained quadratic binary programming, and we resolve it afterward by means of a genetic algorithm. The efficiency of the approach is confirmed by results of numerical experiments on DIMACS benchmarks

Evaluation of the reported data linkage process and associated quality issues for linked routinely collected healthcare data in multimorbidity research: a systematic methodology review

Objective The objective of this systematic review was to examine how the record linkage process is reported in multimorbidity research. Methods A systematic search was conducted in Medline, Web of Science and Embase using predefined search terms, and inclusion and exclusion criteria. Published studies from 2010 to 2020 using linked routinely collected data for multimorbidity research were included. Information was extracted on how the linkage process was reported, which conditions were studied together, which data sources were used, as well as challenges encountered during the linkage process or with the linked dataset. Results Twenty studies were included. Fourteen studies received the linked dataset from a trusted third party. Eight studies reported variables used for the data linkage, while only two studies reported conducting prelinkage checks. The quality of the linkage was only reported by three studies, where two reported linkage rate and one raw linkage figures. Only one study checked for bias by comparing patient characteristics of linked and non-linked records. Conclusions The linkage process was poorly reported in multimorbidity research, even though this might introduce bias and potentially lead to inaccurate inferences drawn from the results. There is therefore a need for increased awareness of linkage bias and transparency of the linkage processes, which could be achieved through better adherence to reporting guidelines. PROSPERO registration number CRD42021243188

Biological Activity of Rosmarinus Officinalis Essential Oils against Callosobruchus Maculatus, (Coleoptera, Bruchinae)

For the purpose of finding alternative ways to synthetic insecticides to fight against pests that ravage stored pulses, rosemary’s (Rosmarinus officinalis (L)) (Lamiaceae) essential oils have been tested against cowpea weevils (Callosobruchus maculatus (Fab)) (Coleoptera, Bruchinae) reared on chickpea (Cicer arietinum (L)) seeds. The chickpea seeds have been infested with ten newly-hatched pairs of cowpea weevils, then fumigated with increasing concentrations of 0, 4, 6, 8 or 10µl of rosemary’s essential oils per liter of air. These essential oils were analyzed by GC-MS. The compound groups were predominantly monoterpenes (93.06%), 74.93% of which were oxygenated and 18.13% hydrocarbonated. The main components in the oxygenated monoterpenes are eucalyptol (1,8-cineol) (50,42%), camphor (17.73%) and borneol (5.99%), while the 3-carene (12.05%) is the most represented compound in the hydrocarbonated  monoterpenes. The remaining constituents represent only 6.94% of essential oils. Rosemary’s essential oils significantly affect longevity (Treated lot: 1 – 7 days, control lot: 2 – 12 days), fecundity (10 – 48 eggs/10 females vs. 437 – 491 eggs/10 females), and fertility (66.67 – 85.00% vs. 93.75 – 95.44%). The cowpea weevil’s success rates in the treated group were 0 – 60.42% compared to 86.35 – 92.33% in the control lot. The lethal concentrations at 50% (LC50) and 99% (CL99), for exposures between 24 and 120h , ranged from 5.51 – 2.43µl/l of air to 11.24 – 6.33µl/l of air, respectively, for males and from 6.80 – 3.04µl/l of air to 15.74 – 7.44µl/l of air for females. The demographic parameters are significantly affected. The average generation lifespan is prolonged ranging from 33.83 days for the control lots to 36.57 days for the treated lots, while the other parameters were all shortened. Rosemary’s essential oils may be used in an Integrated Pest Management (IPM) of stored legumes without any health or environmental risks. Keywords: Essential oils, Rosmarinus officinalis, Callosobruchus maculatus, Pulses, Fumigation

The role of clinical decision support systems in preventing stroke in primary care: a systematic review.

Computerized clinical decision support systems (CDSS) are increasingly being used to facilitate the role of clinicians in complex decision-making processes. This systematic review evaluates evidence of the available CDSS developed and tested to support the decision-making process in primary healthcare for stroke prevention and barriers to practical implementations in primary care settings. A systematic search of Web of Science, Medline Ovid, Embase Ovid, and Cinahl was done. A total of five studies, experimental and observational, were synthesised in this review. This review found that CDSS facilitate decision-making processes in primary health care settings in stroke prevention options. However, barriers were identified in designing, implementing, and using the CDSS

New Methodology for Asynchronous Motor the Adaptive-Sliding-Mode-Control Capable of High Performance Regulation

A new methodology for the design of adaptive sliding mode control (ASMC) for Asynchronous motor control will be presented in this paper. The sliding mode control (SMC) has become one of the most active branches of control theory that has found successful applications in a variety of engineering systems, such an the electrical motors. The new Adaptive sliding mode control method is compared to other existing techniques. The pros and cons of ASMC controller will be demonstrated by intensive simulation results. It will be shown that the presented controller is with fast tracking capability, less steady state error, and robust to load disturbance

Image segmentation using joint spatial-intensity-shape features: Application to CT lung nodule segmentation

Automatic segmentation of medical images is a challenging problem due to the complexity and variability of human anatomy, poor contrast of the object being segmented, and noise resulting from the image acquisition process. This paper presents a novel non-parametric feature analysis method for the segmentation of 3D medical lesions. The proposed algorithm combines 1) a volumetric shape feature (shape index) based on high-order partial derivatives; 2) mean shift clustering in a joint spatial-intensity-shape (JSIS) feature space; and 3) a modified expectation-maximization (MEM) algorithm on the mean shift mode map to merge the neighboring regions (modes). In such a scenario, the volumetric shape feature is integrated into the process of the segmentation algorithm. The joint spatial–intensity-shape features provide rich information for the segmentation of the anatomic structures or lesions (tumors). The proposed method has been evaluated on a clinical dataset of thoracic CT scans that contains 68 nodules. A volume overlap ratio between each segmented nodule and the ground truth annotation is calculated. Using the proposed method, the mean overlap ratio over all the nodules is 0.80. On visual inspection and using a quantitative evaluation, the experimental results demonstrate the potential of the proposed method. It can properly segment a variety of nodules including juxta-vascular and juxta-pleural nodules, which are challenging for conventional methods due to the high similarity of intensities between the nodules and their adjacent tissues. This approach could also be applied to lesion segmentation in other anatomies, such as polyps in the colon

Early diagnostic suggestions improve accuracy of GPs:a randomised controlled trial using computer-simulated patients

Background: Designers of computerised diagnostic support systems (CDSSs) expect physicians to notice when they need advice and enter into the CDSS all information that they have gathered about the patient. The poor use of CDSSs and the tendency not to follow advice once a leading diagnosis emerges would question this expectation.Aim: To determine whether providing GPs with diagnoses to consider before they start testing hypotheses improves accuracy.Design and setting: Mixed factorial design, where 297 GPs diagnosed nine patient cases, differing in difficulty, in one of three experimental conditions: control, early support, or late support.Method: Data were collected over the internet. After reading some initial information about the patient and the reason for encounter, GPs requested further information for diagnosis and management. Those receiving early support were shown a list of possible diagnoses before gathering further information. In late support, GPs first gave a diagnosis and were then shown which other diagnoses they could still not discount.Results: Early support significantly improved diagnostic accuracy over control (odds ratio [OR] 1.31; 95% confidence interval [95%CI] = 1.03 to 1.66, P = 0.027), while late support did not (OR 1.10; 95% CI = 0.88 to 1.37). An absolute improvement of 6% with early support was obtained. There was no significant interaction with case difficulty and no effect of GP experience on accuracy. No differences in information search were detected between experimental conditions.Conclusion: Reminding GPs of diagnoses to consider before they start testing hypotheses can improve diagnostic accuracy irrespective of case difficulty, without lengthening information search

Desensitisation to cigarette package graphic health warnings:a cohort comparison between London and Singapore

OBJECTIVES: We compared 2 sociocultural cohorts with different duration of exposure to graphic health warning labels (GHWL), to investigate a possible desensitisation to their use. We further studied how a differing awareness and emotional impact of smoking-associated risks could be used to prevent this. SETTING: Structured interviews of patients from the general respiratory department were undertaken between 2012 and 2013 in 2 tertiary hospitals in Singapore and London. PARTICIPANTS: 266 participants were studied, 163 Londoners (35% smokers, 54% male, age 52±18 years) and 103 Singaporeans (53% smokers, p=0.003; 78% male, p<0.001; age 58±15 years, p=0.012). MAIN OUTCOMES AND MEASURES: 50 items assessed demographics, smoking history, knowledge and the deterring impact of smoking-associated risks. After showing 10 GHWL, the impact on emotional response, cognitive processing and intended smoking behaviour was recorded. RESULTS: Singaporeans scored lower than the Londoners across all label processing constructs, and this was consistent for the smoking and non-smoking groups. Londoners experienced more ‘disgust’ and felt GHWL were more effective at preventing initiation of, or quitting, smoking. Singaporeans had a lower awareness of lung cancer (82% vs 96%, p<0.001), despite ranking it as the most deterring consequence of smoking. Overall, ‘blindness’ was the least known potential risk (28%), despite being ranked as more deterring than ‘stroke’ and ‘oral cancer’ in all participants. CONCLUSIONS: The length of exposure to GHWL impacts on the effectiveness. However, acknowledging the different levels of awareness and emotional impact of smoking-associated risks within different sociocultural cohorts could be used to maintain their impact

Split operator method for fluorescence diffuse optical tomography using anisotropic diffusion regularisation with prior anatomical information

Fluorescence diffuse optical tomography (fDOT) is an imaging modality that provides images of the fluorochrome distribution within the object of study. The image reconstruction problem is ill-posed and highly underdetermined and, therefore, regularisation techniques need to be used. In this paper we use a nonlinear anisotropic diffusion regularisation term that incorporates anatomical prior information. We introduce a split operator method that reduces the nonlinear inverse problem to two simpler problems, allowing fast and efficient solution of the fDOT problem. We tested our method using simulated, phantom and ex-vivo mouse data, and found that it provides reconstructions with better spatial localisation and size of fluorochrome inclusions than using the standard Tikhonov penalty term