LDR | | 02412nmm uu200457 4500 |
001 | | 000000332341 |
005 | | 20240805170622 |
008 | | 181129s2018 |||||||||||||||||c||eng d |
020 | |
▼a 9780438083431 |
035 | |
▼a (MiAaPQ)AAI10784160 |
035 | |
▼a (MiAaPQ)uchicago:14239 |
040 | |
▼a MiAaPQ
▼c MiAaPQ
▼d 248032 |
082 | 0 |
▼a 616 |
100 | 1 |
▼a Antropova, Natalia. |
245 | 10 |
▼a Deep Learning and Radiomics of Breast Cancer on DCE-MRI in Assessment of Malignancy and Response to Therapy. |
260 | |
▼a [S.l.] :
▼b The University of Chicago.,
▼c 2018 |
260 | 1 |
▼a Ann Arbor :
▼b ProQuest Dissertations & Theses,
▼c 2018 |
300 | |
▼a 143 p. |
500 | |
▼a Source: Dissertation Abstracts International, Volume: 79-11(E), Section: B. |
500 | |
▼a Adviser: Maryellen Giger. |
502 | 1 |
▼a Thesis (Ph.D.)--The University of Chicago, 2018. |
520 | |
▼a Breast cancer is found in one in eight women in the United States and is expected to be the most frequently diagnosed form of cancer among them in 2018. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) plays a significant role in b |
520 | |
▼a Radiomcs has strong potential to lead clinicians towards more accurate and rapid image interpretation. Furthermore, it can serve as a "virtual digital biopsy", allowing for the discovery of relationships between radiomics and the pathology/genom |
520 | |
▼a The research presented the following results. First, the robustness analysis revealed radiomics features that are generalizable across datasets acquired with MRI scanners of two major manufacturers. Specifically, features that characterize lesio |
520 | |
▼a The medical significance of this research is that it has potential to improve DCE-MRI-based breast cancer management. The developed deep learning methods and their fusion with conventional radiomics can reduce human burden and allow for more rap |
590 | |
▼a School code: 0330. |
650 | 4 |
▼a Medical imaging. |
650 | 4 |
▼a Artificial intelligence. |
650 | 4 |
▼a Oncology. |
690 | |
▼a 0574 |
690 | |
▼a 0800 |
690 | |
▼a 0992 |
710 | 20 |
▼a The University of Chicago.
▼b Medical Physics. |
773 | 0 |
▼t Dissertation Abstracts International
▼g 79-11B(E). |
773 | |
▼t Dissertation Abstract International |
790 | |
▼a 0330 |
791 | |
▼a Ph.D. |
792 | |
▼a 2018 |
793 | |
▼a English |
856 | 40 |
▼u http://www.riss.kr/pdu/ddodLink.do?id=T14997249
▼n KERIS |
980 | |
▼a 201812
▼f 2019 |
990 | |
▼a 관리자 |