| LDR | | 00000nmm u2200205 4500 |
| 001 | | 000000330769 |
| 005 | | 20241104153525 |
| 008 | | 181129s2017 ||| | | | eng d |
| 020 | |
▼a 9780438122376 |
| 035 | |
▼a (MiAaPQ)AAI10902869 |
| 040 | |
▼a MiAaPQ
▼c MiAaPQ
▼d 248032 |
| 049 | 1 |
▼f DP |
| 082 | 0 |
▼a 621.3 |
| 100 | 1 |
▼a Xing, Fuyong. |
| 245 | 10 |
▼a High-Throughput Biomedical Image Computing for Digital Health. |
| 260 | |
▼a [S.l.] :
▼b University of Florida.,
▼c 2017 |
| 260 | 1 |
▼a Ann Arbor :
▼b ProQuest Dissertations & Theses,
▼c 2017 |
| 300 | |
▼a 114 p. |
| 500 | |
▼a Source: Dissertation Abstracts International, Volume: 79-11(E), Section: B. |
| 500 | |
▼a Adviser: Lin Yang. |
| 502 | 1 |
▼a Thesis (Ph.D.)--University of Florida, 2017. |
| 520 | |
▼a In biomedical informatics, a large amount of image data has been collected to support clinical diagnosis, treatment decision, and medical prognosis. The large volume and the diversity of informatics across different imaging modalities require ad |
| 520 | |
▼a In this dissertation, we will describe a high-throughput biomedical image computing framework for digital health, focusing on two important topics: object detection and segmentation as well as their applications, image understanding, in medical |
| 590 | |
▼a School code: 0070. |
| 650 | 4 |
▼a Computer engineering. |
| 650 | 4 |
▼a Computer science. |
| 690 | |
▼a 0464 |
| 690 | |
▼a 0984 |
| 710 | 20 |
▼a University of Florida. |
| 773 | 0 |
▼t Dissertation Abstracts International
▼g 79-11B(E). |
| 773 | |
▼t Dissertation Abstract International |
| 790 | |
▼a 0070 |
| 791 | |
▼a Ph.D. |
| 792 | |
▼a 2017 |
| 793 | |
▼a English |
| 856 | 40 |
▼u http://www.riss.kr/pdu/ddodLink.do?id=T15000422
▼n KERIS |
| 980 | |
▼a 201812
▼f 2019 |
| 990 | |
▼a 관리자
▼b 관리자 |