publication . Article . 2019

deteksi region of interest tulang pada citra b mode secara otomatis menggunakan region proposal networks

Tita Karlita; I Made Gede Sunarya; Joko Priambodo; Rika Rokhana; Eko Mulyanto Yuniarno; I Ketut Eddy Purnama; Mauridhi Hery Purnomo;
Open Access
  • Published: 08 Mar 2019 Journal: Jurnal Nasional Teknik Elektro dan Teknologi Informasi (JNTETI), volume 8, page 68 (issn: 2301-4156, eissn: 2460-5719, Copyright policy)
  • Publisher: Universitas Gadjah Mada
Bone imaging using ultrasound is a safe technique since it does not involve ionizing radiation and non-invasive. However, bone detection and localization to find its region of interest (RoI) is a challenging task because b-mode ultrasound images are characterized by high level of noise and reverberation artifacts. The image quality is user-dependent and the boundary between tissues is blurry, which makes it challenging to interpret images. In this paper, the deep learning approach using Region Proposal Networks was implemented to detect bone’s RoI in b-mode images. The Faster Region-based Convolutional Neural Network model was fine-tuned to detect and determine ...
free text keywords: Region of interest, Reverberation, Artificial intelligence, business.industry, business, Computer vision, Ultrasound, Convolutional neural network, Bone imaging, Region proposal, Deep learning, Image quality, Computer science
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