Advanced Sensing and Image Processing Techniques for Healthcare Applications
dc.contributor.editor | Abolghasemi, Vahid | |
dc.contributor.editor | Anisi, Hossein | |
dc.contributor.editor | Ferdowsi, Saideh | |
dc.date.accessioned | 2022-05-06T11:25:28Z | |
dc.date.available | 2022-05-06T11:25:28Z | |
dc.date.issued | 2022 | |
dc.identifier | ONIX_20220506_9783036540320_129 | |
dc.identifier.uri | https://directory.doabooks.org/handle/20.500.12854/81063 | |
dc.description.abstract | This Special Issue aims to attract the latest research and findings in the design, development and experimentation of healthcare-related technologies. This includes, but is not limited to, using novel sensing, imaging, data processing, machine learning, and artificially intelligent devices and algorithms to assist/monitor the elderly, patients, and the disabled population. | |
dc.language | English | |
dc.subject.classification | thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries | en_US |
dc.subject.classification | thema EDItEUR::U Computing and Information Technology::UY Computer science | en_US |
dc.subject.other | tremor | |
dc.subject.other | essential tremor | |
dc.subject.other | ataxia | |
dc.subject.other | finger–nose–finger test | |
dc.subject.other | H&E | |
dc.subject.other | decellularization | |
dc.subject.other | liver | |
dc.subject.other | tissue engineering | |
dc.subject.other | semantic segmentation | |
dc.subject.other | convolutional neural networks | |
dc.subject.other | segmentation | |
dc.subject.other | lung | |
dc.subject.other | CT image | |
dc.subject.other | U-Net | |
dc.subject.other | ResNet-34 | |
dc.subject.other | BConvLSTM | |
dc.subject.other | magnetic resonance images | |
dc.subject.other | brain tissue segmentation | |
dc.subject.other | multi-scale feature learning | |
dc.subject.other | multi-branch pooling | |
dc.subject.other | multi-branch dense prediction | |
dc.subject.other | multi-branch output | |
dc.subject.other | delay-and-sum (DAS) | |
dc.subject.other | delay-multiply-and-sum (DMAS) | |
dc.subject.other | signal coherence | |
dc.subject.other | power doppler detection | |
dc.subject.other | plane-wave (PW) imaging | |
dc.subject.other | complementary subset transmit (CST) | |
dc.subject.other | coherent plane-wave compounding (CPWC) | |
dc.subject.other | robotic cell manipulation | |
dc.subject.other | mechanical properties | |
dc.subject.other | elasticity measurement | |
dc.subject.other | viscosity measurement | |
dc.subject.other | cell mechanics | |
dc.subject.other | hemoglobin sensor | |
dc.subject.other | bladder irrigation monitor | |
dc.subject.other | absorption near infrared | |
dc.subject.other | artificial intelligence | |
dc.subject.other | bubble detection | |
dc.subject.other | exercise | |
dc.subject.other | EEG | |
dc.subject.other | EMG | |
dc.subject.other | ECG | |
dc.subject.other | brain activity | |
dc.subject.other | age | |
dc.subject.other | exercise habit | |
dc.subject.other | tinnitus | |
dc.subject.other | auditory discrimination therapy | |
dc.subject.other | EEG evaluation | |
dc.subject.other | event-related synchronization | |
dc.subject.other | event-related desynchronization | |
dc.subject.other | convolutional neural network | |
dc.subject.other | image registration | |
dc.subject.other | cycle constraint | |
dc.subject.other | multimodal features | |
dc.subject.other | self-supervision | |
dc.subject.other | rigid alignment | |
dc.subject.other | magnetic resonance fingerprinting | |
dc.subject.other | echo-planar imaging | |
dc.subject.other | T1 and T2* relaxation times | |
dc.subject.other | denoising convolutional neural network | |
dc.subject.other | self-attention | |
dc.subject.other | feature pyramid network | |
dc.subject.other | image processing | |
dc.subject.other | object detection | |
dc.subject.other | blind | |
dc.subject.other | braille system | |
dc.subject.other | 3D body shapes | |
dc.subject.other | body weights and measures | |
dc.subject.other | postpartum period | |
dc.subject.other | pregnancy period | |
dc.subject.other | anthropometry | |
dc.subject.other | machine learning | |
dc.subject.other | vital sign | |
dc.subject.other | invasive blood pressure | |
dc.subject.other | feature engineering | |
dc.subject.other | hypotension | |
dc.subject.other | arterial hypotension | |
dc.title | Advanced Sensing and Image Processing Techniques for Healthcare Applications | |
dc.type | book | |
oapen.identifier.doi | 10.3390/books978-3-0365-4031-3 | |
oapen.relation.isPublishedBy | 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 | |
oapen.relation.isbn | 9783036540320 | |
oapen.relation.isbn | 9783036540313 | |
oapen.pages | 258 | |
oapen.place.publication | Basel |
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