DETEKSI RUANG JANTUNG JANIN PADA PANDANGAN 3-VESSEL TRACHEA MENGGUNAKAN ARSITEKTUR FASTER RCNN

GUSENDI, ARJUNO and Nurmaini, Siti (2021) DETEKSI RUANG JANTUNG JANIN PADA PANDANGAN 3-VESSEL TRACHEA MENGGUNAKAN ARSITEKTUR FASTER RCNN. Undergraduate thesis, Sriwijaya University.

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Abstract

The heart chambers are divided into four different chambers, including the Left Atrium (LA), Right Atrium (RA), Left Ventricle (LV) and Right Ventricle (RV). The heart chamber itself can be seen visually using an Ultrasonography (USG) medical device. On ultrasound, the fetal heart has several points of view, including Four Chamber View (4CV), Left Ventricular Outflow Tract (LVOT), Right Venticular Outflow Tract (RVOT), and Three Vessel of Trachea (TVT). In the Three Vessel of Trachea (TVT) view, the images displayed are Ductus Arteriosus (DUCT), Superior Vena Cava (SVC), Aorta (AoA) and Trachea which are detected by using Deep Learning with Faster-RCNN architecture. Faster R-CNN is one method that is often used in object detection. Faster R-CNN consists of a combination of the Fast R-CNN method and the Region Proposal Network (RPN). In this study, there were two detection cases, namely using selection data and data without selection. The number of models from all cases is 14 for tuning the learning rate parameters, the number of epochs and the best backbone. Of the 14 models tested, the best model was obtained using data without selection and Backbone VGG16 learning rare 0.001 epoch 50. The average mean average precision (MAP) obtained with the best model was 87.55%

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Ultrasonography, Three Vessel of Trachea, Faster RCNN, Mean Average Precision
Subjects:	Q Science > Q Science (General) > Q334-342 Computer science. Artificial intelligence. Algorithms. Robotics. Automation.
Divisions:	09-Faculty of Computer Science > 56201-Computer Systems (S1)
Depositing User:	Arjuno Gusendi
Date Deposited:	29 Jul 2021 08:45
Last Modified:	29 Jul 2021 08:45
URI:	http://repository.unsri.ac.id/id/eprint/50986

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