Wheelchair Controlled by Eye Movement Using Raspberry Pi for ALS Patients

Buele, Jorge; Varela-Aldás, José; Salazar, Franklin W.; Soria, Angel; Andaluz, Víctor H.

doi:10.1007/978-3-030-35740-5_9

Cited by 1 publication

(1 citation statement)

References 23 publications

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“…The development of technology and engineering techniques have allowed the dissemination of knowledge in all fields of science [ 1 – 5 ]. Its application in medicine has increased with the aim of improving human health, in the treatment of diseases, making prostheses, developing rehabilitation sessions, during surgeries or in the resuscitation of patients [ 6 – 9 ]. Interesting proposals have been generated using informatics, instrumentation, robotics, automation, image and signal processing, among others [ 10 – 14 ].…”

Section: Introductionmentioning

confidence: 99%

Detection of Thyroid Nodules Through Neural Networks and Processing of Echographic Images

Haro

Toalombo

Galarza

et al. 2020

Computational Science and Its Applications – ICCSA 2020

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The abnormal functioning of hormones produces the appearance of malformations in human bodies that must be detected early. In this manuscript, two proposals are presented for the identification of thyroid nodules in ultrasound images, using convolutional neural networks. For the network training, 400 images obtained from a medical center and stored in a database have been used. Free access software (Python and TensorFlow) has been used as part of the algorithm development, following the stages of image preprocessing, network training, filtering and layer construction. Results graphically present the incidence of people suffering from this health problem. In addition, based on the respective tests, it is identified that the system developed in Python has greater precision and accuracy, 90% and 81% respectively, than TensorFlow design. Through neural networks, the recognition up to 4 mm thyroid nodules is evidenced.

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