278 related articles for article (PubMed ID: 32751433)
1. Efficient Bone Metastasis Diagnosis in Bone Scintigraphy Using a Fast Convolutional Neural Network Architecture.
Papandrianos N; Papageorgiou E; Anagnostis A; Papageorgiou K
Diagnostics (Basel); 2020 Jul; 10(8):. PubMed ID: 32751433
[TBL] [Abstract][Full Text] [Related]
2. 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]
3. 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]
4. A Lightweight Convolutional Neural Network Architecture Applied for Bone Metastasis Classification in Nuclear Medicine: A Case Study on Prostate Cancer Patients.
Ntakolia C; Diamantis DE; Papandrianos N; Moustakidis S; Papageorgiou EI
Healthcare (Basel); 2020 Nov; 8(4):. PubMed ID: 33217973
[TBL] [Abstract][Full Text] [Related]
5. White blood cells detection and classification based on regional convolutional neural networks.
Kutlu H; Avci E; Özyurt F
Med Hypotheses; 2020 Feb; 135():109472. PubMed ID: 31760248
[TBL] [Abstract][Full Text] [Related]
6. Automatic identification of suspicious bone metastatic lesions in bone scintigraphy using convolutional neural network.
Liu Y; Yang P; Pi Y; Jiang L; Zhong X; Cheng J; Xiang Y; Wei J; Li L; Yi Z; Cai H; Zhao Z
BMC Med Imaging; 2021 Sep; 21(1):131. PubMed ID: 34481459
[TBL] [Abstract][Full Text] [Related]
7. Co-trained convolutional neural networks for automated detection of prostate cancer in multi-parametric MRI.
Yang X; Liu C; Wang Z; Yang J; Min HL; Wang L; Cheng KT
Med Image Anal; 2017 Dec; 42():212-227. PubMed ID: 28850876
[TBL] [Abstract][Full Text] [Related]
8. Effect of domain knowledge encoding in CNN model architecture-a prostate cancer study using mpMRI images.
Sobecki P; Jóźwiak R; Sklinda K; Przelaskowski A
PeerJ; 2021; 9():e11006. PubMed ID: 33732553
[TBL] [Abstract][Full Text] [Related]
9. Deep Learning Based Classification of Dermatological Disorders.
AlSuwaidan L
Biomed Eng Comput Biol; 2023; 14():11795972221138470. PubMed ID: 37533697
[TBL] [Abstract][Full Text] [Related]
10. 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]
11. Deep CNN models for pulmonary nodule classification: Model modification, model integration, and transfer learning.
Zhao X; Qi S; Zhang B; Ma H; Qian W; Yao Y; Sun J
J Xray Sci Technol; 2019; 27(4):615-629. PubMed ID: 31227682
[TBL] [Abstract][Full Text] [Related]
12. dSPIC: a deep SPECT image classification network for automated multi-disease, multi-lesion diagnosis.
Lin Q; Cao C; Li T; Man Z; Cao Y; Wang H
BMC Med Imaging; 2021 Aug; 21(1):122. PubMed ID: 34380441
[TBL] [Abstract][Full Text] [Related]
13. Deep learning approaches using 2D and 3D convolutional neural networks for generating male pelvic synthetic computed tomography from magnetic resonance imaging.
Fu J; Yang Y; Singhrao K; Ruan D; Chu FI; Low DA; Lewis JH
Med Phys; 2019 Sep; 46(9):3788-3798. PubMed ID: 31220353
[TBL] [Abstract][Full Text] [Related]
14. Classification of Mammogram Images Using Multiscale all Convolutional Neural Network (MA-CNN).
Agnes SA; Anitha J; Pandian SIA; Peter JD
J Med Syst; 2019 Dec; 44(1):30. PubMed ID: 31838610
[TBL] [Abstract][Full Text] [Related]
15. State-of-the-Art of Breast Cancer Diagnosis in Medical Images via Convolutional Neural Networks (CNNs).
Harrison P; Hasan R; Park K
J Healthc Inform Res; 2023 Dec; 7(4):387-432. PubMed ID: 37927373
[TBL] [Abstract][Full Text] [Related]
16. 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]
17. A deep learning framework for automatic detection of arbitrarily shaped fiducial markers in intrafraction fluoroscopic images.
Mylonas A; Keall PJ; Booth JT; Shieh CC; Eade T; Poulsen PR; Nguyen DT
Med Phys; 2019 May; 46(5):2286-2297. PubMed ID: 30929254
[TBL] [Abstract][Full Text] [Related]
18. Holographic Microwave Image Classification Using a Convolutional Neural Network.
Wang L
Micromachines (Basel); 2022 Nov; 13(12):. PubMed ID: 36557348
[TBL] [Abstract][Full Text] [Related]
19. Distinction between benign and malignant breast masses at breast ultrasound using deep learning method with convolutional neural network.
Fujioka T; Kubota K; Mori M; Kikuchi Y; Katsuta L; Kasahara M; Oda G; Ishiba T; Nakagawa T; Tateishi U
Jpn J Radiol; 2019 Jun; 37(6):466-472. PubMed ID: 30888570
[TBL] [Abstract][Full Text] [Related]
20. Refactoring and performance analysis of the main CNN architectures: using false negative rate minimization to solve the clinical images melanoma detection problem.
Di Biasi L; De Marco F; Auriemma Citarella A; Castrillón-Santana M; Barra P; Tortora G
BMC Bioinformatics; 2023 Oct; 24(1):386. PubMed ID: 37821815
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
