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Two key research issues are addressed: (i) A semantic representation and interpretation framework by using a lightweight self-supervised learning approach, namely the Context-Free Grammar and Push-Down Automaton; and (ii) A mobile phone App implementation of B-mode medical ultrasound imaging with a handheld probe, which can make use of the learned semantic features of scanned images for future home-based health screening.
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Ying Xu, Aurelio Jethro Prohara, Hock Soon Seah, Feng Lin, "Semantic feature representation and interpretation with context-free grammar and push-down automaton," Proc. SPIE 11792, International Forum on Medical Imaging in Asia 2021, 117920S (20 April 2021); https://doi.org/10.1117/12.2588347