Evaluation of IoT Capability in Detecting Kidney Malformations on Ultrasound Imaging System


avatar Ali Hajipourtalebi 1 , avatar Monireh Tahvildarzadeh 2 , avatar Soheila Vashghani Farahani 3 , * , avatar Mehrangiz Ghabimi ORCID 4 , avatar Sadegh Taheri 1

Student Research Committee, Faculty of Nursing, AJA University of Medical Sciences, Tehran, Iran
Health Information Technology Group, Lorestan University of Medical Sciences, Khoramabad, Iran
Student Research Committee, Lorestan University of Medical Sciences, Khoramabad, Iran
Zahedan University of Medical Sciences, Zahedan, Iran

how to cite: Hajipourtalebi A, Tahvildarzadeh M, Vashghani Farahani S, Ghabimi M, Taheri S . Evaluation of IoT Capability in Detecting Kidney Malformations on Ultrasound Imaging System. Innov J Radiol. 2019;16(Special Issue):e99155. https://doi.org/10.5812/iranjradiol.99155.



Remote radiology is used in the remote areas today to diagnose scanned ultrasound data due to the lack of trained radiologists. The availability of online radiography experts and the availability of portable ultrasound communication facilities are some of the issues in remote radiology for the use of ultrasound scanning in telehealth.


The purpose of the present study was to investigate the ability of IoT to detect computer abnormalities of kidneys on ultrasound imaging.


The study was conducted systematically by searching the Scopus, Science Direct, PubMed, and Google Scholar search engine databases using the PRISMA flow diagram to select articles. The English language input and the time range of 2013 to 2018 were used for the search. There were about 123 articles, 42 of which were included in the study. Then, the qualitative evaluation of articles was done based on the 12-question CASP diagnostic test study checklist and finally, 15 articles related to the study were selected.


The results of studies showed that IoT was more acceptable and satisfactory than other imaging modalities and had a significant role in the diagnosis of kidney disease, in terms of both cost and time.


The results of the study showed that in the absence of a radiologist in the therapeutic environment or the patient’s inability to visit the hospital or clinic, using IoT is the best way to solve the mentioned problems.
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