The utility of mHealth in Medical Imaging

Perera, Chandrashan; Chakrabarti, Rahul

doi:10.7309/jmtm.2.3.2

Cited by 7 publications

(6 citation statements)

References 17 publications

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“…Depending on the type of injury and the affected area, we classified the photographs as: close-up, taken at the closest possible distance (generally about 10 cm from the lesion); taken at medium distance (approximately 30 cm away from the lesion), which included identifying anatomical elements; and long or general view, in which the image contained the lesions plus approximately 20% of healthy skin surface. 24 The images were transferred to a Google Forms online survey and the 22 cases were randomized and numbered for inclusion in the survey. The approval of the Clinical Research Ethics Committee of the Foundation University Institute for Primary Health Care Research Jordi Gol i Gurina (P18/046) was obtained for the study.…”

Section: Methodsmentioning

confidence: 99%

Diagnosis of Skin Lesions Using Photographs Taken With a Mobile Phone: An Online Survey of Primary Care Physicians

Marín-Gomez

Vidal-Alaball

Roura-Poch

et al. 2020

J Prim Care Community Health

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Skin conditions are one of the most frequent reasons for visiting a primary health care facility, making it of vital importance that general practitioners (GPs) have the right knowledge and tools to diagnose the most frequent dermatological conditions. Methods: This study evaluates the accuracy of dermatological diagnoses made by 120 GPs based on photographs taken with a smartphone by an anonymous online cross-sectional survey. Results: The study was carried out between August and October 2018. The results show that the majority of the participants are in favor of using mobile phones to communicate with other professionals and use them to consult medical images. The majority (69%) took dermatological photographs and the preferred device was a smartphone (70%). From 22 different images evaluated, in 69% of responses, participants expressed a high degree of confidence in their ability to diagnose the lesion shown and in 72% of the cases, the diagnosis chosen was correct. Conclusions: The study confirms that the use of smartphone to send medical images is growing rapidly and its potential for taking medical images is an opportunity to help primary care teams deal with dermatological problems. The results suggest that GPs need further training in interpreting dermatological images, to increase their diagnostic confidence and to avoid the need for referrals to face-to-face visits.

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Section: Methodsmentioning

confidence: 99%

Diagnosis of Skin Lesions Using Photographs Taken With a Mobile Phone: An Online Survey of Primary Care Physicians

Marín-Gomez

Vidal-Alaball

Roura-Poch

et al. 2020

J Prim Care Community Health

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“…Telecommunication technologies, especially mobile phones have contributed greatly to the successful implementation of mHealth initiatives. The popularity of smartphones to the global population, its computing capabilities and affordability have made it an effective tool for disseminating health care (28,29). mHealth cardiology applications have generally been utilized for the following purposes: monitoring, selfmanagement, reporting, adherence and rehabilitation.…”

Section: Rural Healthcare Telemedicine and Mobile Health (Mhealth)mentioning

confidence: 99%

Deep learning for cardiac computer-aided diagnosis: benefits, issues & solutions

Loh¹,

Then²

2017

mHealth

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Cardiovascular diseases are one of the top causes of deaths worldwide. In developing nations and rural areas, difficulties with diagnosis and treatment are made worse due to the deficiency of healthcare facilities. A viable solution to this issue is telemedicine, which involves delivering health care and sharing medical knowledge at a distance. Additionally, mHealth, the utilization of mobile devices for medical care, has also proven to be a feasible choice. The integration of telemedicine, mHealth and computer-aided diagnosis systems with the fields of machine and deep learning has enabled the creation of effective services that are adaptable to a multitude of scenarios. The objective of this review is to provide an overview of heart disease diagnosis and management, especially within the context of rural healthcare, as well as discuss the benefits, issues and solutions of implementing deep learning algorithms to improve the efficacy of relevant medical applications.

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“…Nowadays, the use of smartphones equipped with camera and various sensors is very common the people and these equipments are practical for wound measurement (Wannous et al, 2011;Cuautle, 2007;Foltynski et al, 2013;Hettiarachchi et al, 2013;Perera and Chakrabarti, 2013;Sikka et al, 2012). These devices can improve the telemedicine techniques and treatment at distance (Vivanco et al, 2011).…”

Section: Related Workmentioning

confidence: 99%

“…Recently, many authors developed various frameworks to estimate the wound area using the Java programming language (Cuautle, 2007), and XML (eXtended Markup Language) descriptors (Prodan et al, 2009;Prodan et al, 2006) as reference, for Android platform or other mobile platforms. The mobile health improves the treatments in various areas, such as control of a healing wound and the patient's health state in various parameters (Friesen et al, 2013, Perera andChakrabarti, 2013). For desktop applications, mobile applications or webbased applications, this needs a study and development of a framework for the programming language used and an image descriptor (in general, it is defined in XML) for classifying the images.…”

Section: Related Workmentioning

confidence: 99%

“…The mobile applications for estimating the wound area have a lot of research that explain the benefits of these applications (Perera and Chakrabarti, 2013;Friesen et al, 2013;Casas et al, 2011). About the method analyzed in the section 3, ruler measures and transparency tracings were used by authors of (Nemeth et al, 2010) for measuring wound size often have low accuracy and reliability and they created a new method used in a wound measurement device (WMD) designed by them.…”

Section: Wound Area Estimation Using a Mobile Devicementioning

confidence: 99%

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Wound Area Assessment using Mobile Application

Pires

García

2015

Proceedings of the International Conference on Biomedical Electronics and Devices

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This research aims to discover methods for the detection of the area of a wound using mobile devices. These devices have low memory and low processing capacity and they need the use of low complexity operations to identify a wound. The calculation of the wounded area consists of three phases, there are: image acquisition, image processing, surface reconstruction and calculations. This research is related to the use a mobile device to identify wound contours and area in a captured image. This image can be captured with a camera in a smartphone and the wound area is calculated based on the distance of the surface area and the resolution of the image captured. The main study in this research is the image processing in a mobile device, due to the limitations of these devices. However, the application developed during this research was developed for desktop, using the OpenCV library that is compatible with the Android platform and Java desktop technologies. During this research, the developed code written in Java will be easily adapted to the Android platform. The desktop application developed is available in a free repository for testing.

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The utility of mHealth in Medical Imaging

Cited by 7 publications

References 17 publications

Diagnosis of Skin Lesions Using Photographs Taken With a Mobile Phone: An Online Survey of Primary Care Physicians

Diagnosis of Skin Lesions Using Photographs Taken With a Mobile Phone: An Online Survey of Primary Care Physicians

Deep learning for cardiac computer-aided diagnosis: benefits, issues & solutions

Wound Area Assessment using Mobile Application

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