Please use this identifier to cite or link to this item: https://dspace.ctu.edu.vn/jspui/handle/123456789/94528
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dc.contributor.advisorNguyễn, Thanh Hải-
dc.contributor.authorNguyễn, Chí Bảo-
dc.date.accessioned2024-01-10T07:52:55Z-
dc.date.available2024-01-10T07:52:55Z-
dc.date.issued2023-
dc.identifier.otherB1910619-
dc.identifier.urihttps://dspace.ctu.edu.vn/jspui/handle/123456789/94528-
dc.description46 Trvi_VN
dc.description.abstractHand fractures are easy to occur in everyday life, especially for those who often participate in sporting and working activities. Hand fractures are not too dangerous, but they directly affect daily life, causing many inconveniences. If not treated promptly or misdiagnosed, it will cause a loss of aesthetics, affecting the function of grasping and tactile ability to recognize objects later. With a diagnosis of a hand fracture, medical practitioners often order an X-ray because they can see details about the fracture line, fracture pattern, and soft tissue damage. Based on that, doctors will use appropriate treatment methods. This study examined the performance of diagnosing bone fractures, detect the location and shape of cracks based on two methods: instance segmentation and semantic segmentation. The results obtained in diagnosing fractures are 96,73%.vi_VN
dc.language.isoenvi_VN
dc.publisherTrường Đại Học Cần Thơvi_VN
dc.subjectCÔNG NGHỆ THÔNG TIN - CHẤT LƯỢNG CAOvi_VN
dc.titleAN APPROACH FOR HAND BONE FRACTURE DETECTION IN X-RAY IMAGES WITH DEEP LEARNING TECHNIQUESvi_VN
dc.title.alternativePHƯƠNG PHÁP PHÁT HIỆN GÃY XƯƠNG BÀN TAY TRONG HÌNH ẢNH X-QUANG BẰNG KỸ THUẬT HỌC SÂUvi_VN
dc.typeThesisvi_VN
Appears in Collections:Trường Công nghệ Thông tin & Truyền thông

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