Cited time in webofscience Cited time in scopus

Full metadata record

DC Field Value Language
dc.contributor.advisor 황재윤 -
dc.contributor.author Kim, Jae Seong -
dc.date.accessioned 2022-03-07T16:00:12Z -
dc.date.available 2022-03-07T16:00:12Z -
dc.date.issued 2022 -
dc.identifier.uri http://dgist.dcollection.net/common/orgView/200000591941 en_US
dc.identifier.uri http://hdl.handle.net/20.500.11750/16274 -
dc.description Ultrasound capsule endoscope, Ultrasound imaging, Dual-frequency, Deep learning -
dc.description.statementofresponsibility N -
dc.description.tableofcontents I. Introduction 1
1.1 Motivation 1
1.2 Backgrounds 3
1.2.1 Basic principles of ultrasound 3
1.2.2 Ultrasound B-mode imaging 7
1.2.3 Image enhancement in ultrasound imaging 8
II. Materials and Methods 12
2.1 System configuration 12
2.2 Capsule design 15
2.3 Ultrasound transducer fabrication 17
2.4 Ultrasound imaging 20
2.5 Deep learning network 21
2.6 Quantitative analysis and Evaluation method 25
III. Results and Discussions 29
3.1 Evaluation of the proposed system 29
3.1.1 Penetration depth according to the center frequency 30
3.1.2 Spatial resolution 32
3.1.3 Quality improvement 33
3.1.4 Structural similarity index 36
IV. Conclusion 38
V. Reference 40
요 약 문 43
-
dc.format.extent 43 -
dc.language eng -
dc.publisher DGIST -
dc.subject Ultrasound capsule endoscope, Ultrasound imaging, Dual-frequency, Deep learning -
dc.title Dual-frequency Capsule Type Ultrasound Endoscopic System for Deep Learning-based High-resolution In-depth Imaging -
dc.type Thesis -
dc.identifier.doi 10.22677/thesis.200000591941 -
dc.description.degree Master -
dc.contributor.department Information and Communication Engineering -
dc.contributor.coadvisor Im, Sunghoon -
dc.date.awarded 2022/02 -
dc.publisher.location Daegu -
dc.description.database dCollection -
dc.citation XT.IM 김73 202202 -
dc.date.accepted 1/21/22 -
dc.contributor.alternativeDepartment 정보통신융합전공 -
dc.embargo.liftdate 20230228 -
dc.contributor.affiliatedAuthor Kim, Jae Seong -
dc.contributor.affiliatedAuthor Hwang, Jae Youn -
dc.contributor.affiliatedAuthor Im, Sunghoon -
dc.contributor.alternativeName 김재성 -
dc.contributor.alternativeName Hwang, Jae Youn -
dc.contributor.alternativeName 임성훈 -
Files in This Item:

There are no files associated with this item.

Appears in Collections:
Department of Electrical Engineering and Computer Science Theses Master

qrcode

  • twitter
  • facebook
  • mendeley

Items in Repository are protected by copyright, with all rights reserved, unless otherwise indicated.

BROWSE