Comparison of machine learning strategies for infrared thermography of skin cancer

Objective: The aim of this work was to explore the potential of infrared thermal imaging as an aiding tool for the diagnosis of skin cancer lesions, using artificial intelligence methods. Methods: Thermal parameters of skin tumours were retrieved from thermograms and used as input features for two machine learning based strategies: ensemble learning and deep learning. Results: The deep learning strategy outperformed the ensemble learning one, showing good predictive performance for the differentiation of melanoma and nevi (Precision = 0.9665, Recall = 0.9411, f1-score = 0.9536, ROC(AUC) = 0.9185) and melanoma and non-melanoma skin cancer (Precision = 0.9259, Recall = 0.8852, f1score = 0.9051, ROC(AUC) = 0.901). Conclusion: IRT imaging combined with deep learning techniques is promising for simplifying and accelerating the diagnosis of skin cancer. Significance: Despite ongoing awareness campaigns for skin cancer' risk factors, its incidence rate has continuously been growing worldwide, becoming a major public health issue. The standard first detection method - dermoscopy -, is largely experience-dependent and mostly used to assess melanocytic lesions. As infrared thermal imaging is an innocuous imaging technique that maps skin surface temperature, which may be associated to pathological states, e.g., tumorous lesions, it could be a potential aiding tool for all skin cancer conditions. The application of artificial intelligence methods to process the collected temperature data can save time and assist health care professionals with low experience levels in the diagnosis task. To the best of our knowledge, this is the first study where a data set of skin cancer thermograms is expanded and used for skin lesion differentiation with a deep learning approach

Evaluation of thermal pattern distributions in racehorse saddles using infrared thermography

The impact of a rider’s and saddle’s mass on saddle thermal pattern distribution was evalu ated using infrared thermography (IRT). Eighteen racehorses were ridden by four riders with their own saddle. Images of the saddle panels were captured at each of six thermographic examinations. On each image, six regions of interest (ROIs) were marked on the saddle panels. The mean temperature for each ROI was extracted. To evaluate the influence of load on saddle fit, 4 indicators were used: ΔTmax (difference between the mean temperature of the warmest and coolest ROI); standard deviation of the mean temperature of the six ROIs; right/left; bridging/rocking and front/back thermal pattern indicator. Incorrect saddle fit was found in 25 measurements (23.1%) with ΔTmax greater than 2˚C. The relationships between rider and saddle fit as well as saddle fit and horse were significant (p<0.001). An average ΔTmax in rider A was significantly higher than in other riders (p<0.001). The right/left thermal pattern differed significantly from the optimal value for riders A and B; while the bridging/rocking thermal pattern differed significantly from this value for riders A, C and D (p<0.05). Front saddle thermal pattern was most frequent for rider A (41.5%), whereas back saddle thermal pattern was most frequent for rider C (85.7%). Measurement of the mean temperature in 6 ROIs on saddle panels after training was helpful in assessing the influence of rider and saddle mass on saddle fit. IRT offered a non-invasive, rapid and simple method for assessing load on thermal pattern distribution in race saddles.info:eu-repo/semantics/publishedVersio

PET-MRI in Neuroimaging: technique role in Alzheimer Disease

- Hybrid or multimodal imaging has providedexcellent opportunities to meet the needs inherent in themanagement of neurodegenerative diseases, especially inAlzheimer Disease context. PET-MRI equipment forsimultaneous data acquisition attempts to address thischallenge by bridging the limitations of PET-CT at thebrain level and improving the results achieved through asimultaneous real-time combination of quantitativeneurophysiological information from PET and accurateMRI morphological information, with greaterradiological safety. Therefore, the PET-MRI techniquepresents high potential for diagnostic and follow-upstudies. The aim of this review was to compile the mainadvantages related with PET-MRI along with thedetection of the main challenges which remain to beresolved for a full clinical validation of the technique inNeuroimaging field are identified

A different approach in an AAL ecosystem: a mobile assistant for the caregiver

Currently the Ambient Assisted Living and the Ambient Intelligence areas are very prolific. There is a demand of security and comfort that should be ensured at people’s homes. The AAL4ALL (ambient assisted living for all) pro-ject aims to develop a unified ecosystem and a certification process, allowing the development of fully compatible devices and services. The UserAccess emerges from the AAL4ALL project, being a demonstration of its validity. The UserAc-cess architecture, implementation, interfaces and test scenario are presented, along with the sensor platform specially developed for the AAL4ALL project.Project "AAL4ALL", co-financed by the European Community Fund FEDER, through COMPETE - Programa Operacional Factores de Competitividade (POFC). Foundation for Science and Technology (FCT), Lisbon, Portugal, through Project PEst-C/CTM/LA0025/2013 and the project PEst-OE/EEI/UI0752/2014. Project CAMCoF - Context-aware Multimodal Communication Framework funded by ERDF -European Regional Development Fund through the COMPETE Programme (operational programme for competitiveness) and by National Funds through the FCT - Fundação para a Ciência e a Tecnologia (Portuguese Foundation for Science and Technology) within project FCOMP-01-0124-FEDER-028980

Using thermal imaging to monitor the treatment of latent myofascial trigger points in the upper trapezius

Abstract Clinically, latent myofascial trigger points are characterized as hyperirritable points located within taut bands of skeletal muscles or fascia. These points may cause referred pain, local tenderness and autonomic changes when manually stimulated. Dry needling is one of the treatment options but evidence of its results is scarce. This paper experimentally investigates the potential use of thermal imaging to assess the effect of dry needling on the skin temperature in patients with latent myofascial trigger points. No significant differences were found between the mean skin temperature and pain before and after the treatment, evidencing the agreement between the outcome measures

An AAL collaborative system: the AAL4ALL and a mobile assistant case study

"15th IFIP WG 5.5 Working Conference on Virtual Enterprises, PRO-VE 2014, Amsterdam, The Netherlands, October 6-8, 2014"The areas of Ambient Assisted Living (AAL) and Intelligent Systems (IS) are in full development, but there are still some issues to be resolved. One issue is the myriad of user oriented solutions that are rarely built to interact or integrate with other systems available in the market. In this paper we present the AAL4ALL project and the UserAccess implementation, showing a novel approach towards virtual organizations, interoperability and certification. The aim of this project is to provide a collaborative network of services and devices that connect every user and product from other developers, building a heterogeneous ecosystem. Thus establishing an environment for collaborative care systems, which may be available to the users in from of safety services, comfort services and healthcare services.Project "AAL4ALL", co-financed by the European Community Fund FEDER, through COMPETE - Programa Operacional Factores de Competitividade (POFC). Foundation for Science and Technology (FCT), Lisbon, Portugal, through Project PEst-C/CTM/LA0025/2013 and the project PEst-OE/EEI/UI0752/2014. Project CAMCoF - Context-aware Multimodal Communication Framework fund-ed by ERDF -European Regional Development Fund through the COMPETE Pro-gramme (operational programme for competitiveness) and by National Funds through the FCT - Fundação para a Ciência e a Tecnologia (Portuguese Foundation for Science and Technology) within project FCOMP-01-0124-FEDER-028980

Development of high-resolution infrared thermographic imaging method as a diagnostic tool for acute undifferentiated limp in young children

Acute limp is a common presenting condition in the paediatric emergency department. There are a number of causes of acute limp that include traumatic injury, infection and malignancy. These causes in young children are not easily distinguished. In this pilot study, an infrared thermographic imaging technique to diagnose acute undifferentiated limp in young children was developed. Following required ethics approval, 30 children (mean age = 5.2 years, standard deviation = 3.3 years) were recruited. The exposed lower limbs of participants were imaged using a high-resolution thermal camera. Using predefined regions of interest (ROI), any skin surface temperature difference between the healthy and affected legs was statistically analysed, with the aim of identifying limp. In all examined ROIs, the median skin surface temperature for the affected limb was higher than that of the healthy limb. The small sample size recruited for each group, however, meant that the statistical tests of significant difference need to be interpreted in this context. Thermal imaging showed potential in helping with the diagnosis of acute limp in children. Repeating a similar study with a larger sample size will be beneficial to establish reproducibility of the results