178 related articles for article (PubMed ID: 36334360)
1. BS-80K: The first large open-access dataset of bone scan images.
Huang Z; Pu X; Tang G; Ping M; Jiang G; Wang M; Wei X; Ren Y
Comput Biol Med; 2022 Dec; 151(Pt A):106221. PubMed ID: 36334360
[TBL] [Abstract][Full Text] [Related]
2. Bone metastasis classification using whole body images from prostate cancer patients based on convolutional neural networks application.
Papandrianos N; Papageorgiou E; Anagnostis A; Papageorgiou K
PLoS One; 2020; 15(8):e0237213. PubMed ID: 32797099
[TBL] [Abstract][Full Text] [Related]
3. Development of a computer-aided diagnostic scheme for detection of interval changes in successive whole-body bone scans.
Shiraishi J; Li Q; Appelbaum D; Pu Y; Doi K
Med Phys; 2007 Jan; 34(1):25-36. PubMed ID: 17278486
[TBL] [Abstract][Full Text] [Related]
4. Diagnostic performance of a computer-assisted diagnostic system: sensitivity of BONENAVI for bone scintigraphy in patients with disseminated skeletal metastasis is not so high.
Koizumi M; Motegi K; Koyama M; Ishiyama M; Togawa T; Makino T; Arisaka Y; Terauchi T
Ann Nucl Med; 2020 Mar; 34(3):200-211. PubMed ID: 31970706
[TBL] [Abstract][Full Text] [Related]
5. More advantages in detecting bone and soft tissue metastases from prostate cancer using
Pianou NK; Stavrou PZ; Vlontzou E; Rondogianni P; Exarhos DN; Datseris IE
Hell J Nucl Med; 2019; 22(1):6-9. PubMed ID: 30843003
[TBL] [Abstract][Full Text] [Related]
6. mSegResRF-SPECT: A Novel Joint Classification Model of Whole Body Bone Scan Images for Bone Metastasis Diagnosis.
Ji B; He G; Wen J; Chen Z; Zhao L
Curr Med Imaging; 2024 Feb; ():. PubMed ID: 38415481
[TBL] [Abstract][Full Text] [Related]
7. Computer-aided detection of bone metastasis in bone scintigraphy images using parallelepiped classification method.
Elfarra FG; Calin MA; Parasca SV
Ann Nucl Med; 2019 Nov; 33(11):866-874. PubMed ID: 31493203
[TBL] [Abstract][Full Text] [Related]
8. Automatic creation of annotations for chest radiographs based on the positional information extracted from radiographic image reports.
Wang B; Takeda T; Sugimoto K; Zhang J; Wada S; Konishi S; Manabe S; Okada K; Matsumura Y
Comput Methods Programs Biomed; 2021 Sep; 209():106331. PubMed ID: 34418813
[TBL] [Abstract][Full Text] [Related]
9. Diagnostic performance of a computer-assisted diagnosis system for bone scintigraphy of newly developed skeletal metastasis in prostate cancer patients: search for low-sensitivity subgroups.
Koizumi M; Motegi K; Koyama M; Terauchi T; Yuasa T; Yonese J
Ann Nucl Med; 2017 Aug; 31(7):521-528. PubMed ID: 28456877
[TBL] [Abstract][Full Text] [Related]
10. Diagnostic accuracy of bone metastases detection in cancer patients: comparison between bone scintigraphy and whole-body FDG-PET.
Fujimoto R; Higashi T; Nakamoto Y; Hara T; Lyshchik A; Ishizu K; Kawashima H; Kawase S; Fujita T; Saga T; Togashi K
Ann Nucl Med; 2006 Jul; 20(6):399-408. PubMed ID: 16922468
[TBL] [Abstract][Full Text] [Related]
11. Two-stage framework for optic disc localization and glaucoma classification in retinal fundus images using deep learning.
Bajwa MN; Malik MI; Siddiqui SA; Dengel A; Shafait F; Neumeier W; Ahmed S
BMC Med Inform Decis Mak; 2019 Jul; 19(1):136. PubMed ID: 31315618
[TBL] [Abstract][Full Text] [Related]
12. Development of Convolutional Neural Networks to identify bone metastasis for prostate cancer patients in bone scintigraphy.
Papandrianos N; Papageorgiou EI; Anagnostis A
Ann Nucl Med; 2020 Nov; 34(11):824-832. PubMed ID: 32839920
[TBL] [Abstract][Full Text] [Related]
13. [Usefulness of spatially adaptive noise reduction processing in computer-assisted diagnosis system for bone scintigraphy].
Ichikawa H; Onoguchi M; Okuda K; Kato T; Terabe M; Shimada H
Nihon Hoshasen Gijutsu Gakkai Zasshi; 2014 May; 70(5):461-6. PubMed ID: 24858291
[TBL] [Abstract][Full Text] [Related]
14. Automated diagnosis of bone metastasis based on multi-view bone scans using attention-augmented deep neural networks.
Pi Y; Zhao Z; Xiang Y; Li Y; Cai H; Yi Z
Med Image Anal; 2020 Oct; 65():101784. PubMed ID: 32763793
[TBL] [Abstract][Full Text] [Related]
15. A real use case of semi-supervised learning for mammogram classification in a local clinic of Costa Rica.
Calderon-Ramirez S; Murillo-Hernandez D; Rojas-Salazar K; Elizondo D; Yang S; Moemeni A; Molina-Cabello M
Med Biol Eng Comput; 2022 Apr; 60(4):1159-1175. PubMed ID: 35239108
[TBL] [Abstract][Full Text] [Related]
16. Deep neural network based artificial intelligence assisted diagnosis of bone scintigraphy for cancer bone metastasis.
Zhao Z; Pi Y; Jiang L; Xiang Y; Wei J; Yang P; Zhang W; Zhong X; Zhou K; Li Y; Li L; Yi Z; Cai H
Sci Rep; 2020 Oct; 10(1):17046. PubMed ID: 33046779
[TBL] [Abstract][Full Text] [Related]
17. Diagnostic utility of a computer-aided diagnosis system for whole-body bone scintigraphy to detect bone metastasis in breast cancer patients.
Urano M; Maki Y; Nishikawa H; Kawai T; Shiraki N; Shibamoto Y
Ann Nucl Med; 2017 Jan; 31(1):40-45. PubMed ID: 27686468
[TBL] [Abstract][Full Text] [Related]
18. Evaluation of a revised version of computer-assisted diagnosis system, BONENAVI version 2.1.7, for bone scintigraphy in cancer patients.
Koizumi M; Miyaji N; Murata T; Motegi K; Miwa K; Koyama M; Terauchi T; Wagatsuma K; Kawakami K; Richter J
Ann Nucl Med; 2015 Oct; 29(8):659-65. PubMed ID: 26033528
[TBL] [Abstract][Full Text] [Related]
19. [Diagnostic value of whole-body MRI and bone scintigraphy in the detection of osseous metastases in patients with breast cancer--A Prospective Double-Blinded Study at two Hospital Centers].
Ohlmann-Knafo S; Kirschbaum M; Fenzl G; Pickuth D
Rofo; 2009 Mar; 181(3):255-63. PubMed ID: 19229791
[TBL] [Abstract][Full Text] [Related]
20. Evaluation of a computer-assisted diagnosis system, BONENAVI version 2, for bone scintigraphy in cancer patients in a routine clinical setting.
Koizumi M; Wagatsuma K; Miyaji N; Murata T; Miwa K; Takiguchi T; Makino T; Koyama M
Ann Nucl Med; 2015 Feb; 29(2):138-48. PubMed ID: 25326907
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
