146 related articles for article (PubMed ID: 33730031)
1. Complementary performances of convolutional and capsule neural networks on classifying microfluidic images of dividing yeast cells.
Ghafari M; Clark J; Guo HB; Yu R; Sun Y; Dang W; Qin H
PLoS One; 2021; 16(3):e0246988. PubMed ID: 33730031
[TBL] [Abstract][Full Text] [Related]
2. A computer vision and residual neural network (ResNet) combined method for automated and accurate yeast replicative aging analysis of high-throughput microfluidic single-cell images.
Xiao Q; Wang Y; Fan J; Yi Z; Hong H; Xie X; Huang QA; Fu J; Ouyang J; Zhao X; Wang Z; Zhu Z
Biosens Bioelectron; 2024 Jan; 244():115807. PubMed ID: 37948914
[TBL] [Abstract][Full Text] [Related]
3. Skin lesion classification with ensembles of deep convolutional neural networks.
Harangi B
J Biomed Inform; 2018 Oct; 86():25-32. PubMed ID: 30103029
[TBL] [Abstract][Full Text] [Related]
4. LiverNet: efficient and robust deep learning model for automatic diagnosis of sub-types of liver hepatocellular carcinoma cancer from H&E stained liver histopathology images.
Aatresh AA; Alabhya K; Lal S; Kini J; Saxena PUP
Int J Comput Assist Radiol Surg; 2021 Sep; 16(9):1549-1563. PubMed ID: 34053009
[TBL] [Abstract][Full Text] [Related]
5. Recognition of peripheral blood cell images using convolutional neural networks.
Acevedo A; Alférez S; Merino A; Puigví L; Rodellar J
Comput Methods Programs Biomed; 2019 Oct; 180():105020. PubMed ID: 31425939
[TBL] [Abstract][Full Text] [Related]
6. An experimental study on breast lesion detection and classification from ultrasound images using deep learning architectures.
Cao Z; Duan L; Yang G; Yue T; Chen Q
BMC Med Imaging; 2019 Jul; 19(1):51. PubMed ID: 31262255
[TBL] [Abstract][Full Text] [Related]
7. 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]
8. Classification of white blood cells using capsule networks.
Baydilli YY; Atila Ü
Comput Med Imaging Graph; 2020 Mar; 80():101699. PubMed ID: 32000087
[TBL] [Abstract][Full Text] [Related]
9. Deep learning for patient-specific quality assurance: Identifying errors in radiotherapy delivery by radiomic analysis of gamma images with convolutional neural networks.
Nyflot MJ; Thammasorn P; Wootton LS; Ford EC; Chaovalitwongse WA
Med Phys; 2019 Feb; 46(2):456-464. PubMed ID: 30548601
[TBL] [Abstract][Full Text] [Related]
10. CheXLocNet: Automatic localization of pneumothorax in chest radiographs using deep convolutional neural networks.
Wang H; Gu H; Qin P; Wang J
PLoS One; 2020; 15(11):e0242013. PubMed ID: 33166371
[TBL] [Abstract][Full Text] [Related]
11. Multi-View Ensemble Convolutional Neural Network to Improve Classification of Pneumonia in Low Contrast Chest X-Ray Images.
Ferreira JR; Armando Cardona Cardenas D; Moreno RA; de Fatima de Sa Rebelo M; Krieger JE; Antonio Gutierrez M
Annu Int Conf IEEE Eng Med Biol Soc; 2020 Jul; 2020():1238-1241. PubMed ID: 33018211
[TBL] [Abstract][Full Text] [Related]
12. DetecDiv, a generalist deep-learning platform for automated cell division tracking and survival analysis.
Aspert T; Hentsch D; Charvin G
Elife; 2022 Aug; 11():. PubMed ID: 35976090
[TBL] [Abstract][Full Text] [Related]
13. An Ensemble of Fine-Tuned Convolutional Neural Networks for Medical Image Classification.
Kumar A; Kim J; Lyndon D; Fulham M; Feng D
IEEE J Biomed Health Inform; 2017 Jan; 21(1):31-40. PubMed ID: 28114041
[TBL] [Abstract][Full Text] [Related]
14. Fast and Accurate Detection of COVID-19 Along With 14 Other Chest Pathologies Using a Multi-Level Classification: Algorithm Development and Validation Study.
Albahli S; Yar GNAH
J Med Internet Res; 2021 Feb; 23(2):e23693. PubMed ID: 33529154
[TBL] [Abstract][Full Text] [Related]
15. Automated classification of gastric neoplasms in endoscopic images using a convolutional neural network.
Cho BJ; Bang CS; Park SW; Yang YJ; Seo SI; Lim H; Shin WG; Hong JT; Yoo YT; Hong SH; Choi JH; Lee JJ; Baik GH
Endoscopy; 2019 Dec; 51(12):1121-1129. PubMed ID: 31443108
[TBL] [Abstract][Full Text] [Related]
16. 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]
17. The effects of physics-based data augmentation on the generalizability of deep neural networks: Demonstration on nodule false-positive reduction.
Omigbodun AO; Noo F; McNitt-Gray M; Hsu W; Hsieh SS
Med Phys; 2019 Oct; 46(10):4563-4574. PubMed ID: 31396974
[TBL] [Abstract][Full Text] [Related]
18. Diagnostic accuracy of content-based dermatoscopic image retrieval with deep classification features.
Tschandl P; Argenziano G; Razmara M; Yap J
Br J Dermatol; 2019 Jul; 181(1):155-165. PubMed ID: 30207594
[TBL] [Abstract][Full Text] [Related]
19. Neural network control of focal position during time-lapse microscopy of cells.
Wei L; Roberts E
Sci Rep; 2018 May; 8(1):7313. PubMed ID: 29743647
[TBL] [Abstract][Full Text] [Related]
20. Deep Learning-Based Gleason Grading of Prostate Cancer From Histopathology Images-Role of Multiscale Decision Aggregation and Data Augmentation.
Karimi D; Nir G; Fazli L; Black PC; Goldenberg L; Salcudean SE
IEEE J Biomed Health Inform; 2020 May; 24(5):1413-1426. PubMed ID: 31567104
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]