Page 95 - sjsi
P. 95
Research Article: Alsibai & Heydari 95
5. Azziz R. PCOS: a diagnostic challenge. Reproductive 20. Deng J, Socher R, et al. ImageNet: A large-scale
BioMedicine Online. 2004 April 5; 8(6): 644-648. hierarchical image database. IEEE Conference on
6. Battaglia C, Mancini F, et al. Ultrasound evaluation of Computer Vision and Pattern Recognition. 2009.
PCO, PCOS and OHSS. Reproductive BioMedicine 21. Sharma S, Mehra R. Conventional Machine Learning
Online. 2004; 9(6): 614-619. and Deep Learning Approach for MultiClassification
7. Wang Y, Ge X, et al. Deep Learning in Medical of Breast Cancer Histopathology Images—a
Ultrasound Image Analysis: A Review. IEEE Access. Comparative Insight. J Digit Imaging 2020, 33.
2021; 9: 54310-54324. 22. Gupta A, Ramanath R. Adam vs. SGD: Closing the
8. Diaz-Escobar J, Ordorez-Guillen NE, et al. Deep- generalization gap on image classification. OPT2021:
learning based detection of COVID-19 using lung 13th Annual Workshop on Optimization for Machine
ultrasound imagery. PLoS ONE 16(8): e0255886. Learning. .
2021. 23. Adiwijaya, Unitary NW, Astuti W. Polycystic Ovary
9. Carneiro G, Nascimento JC, Freitas A. The Ultrasound Images Dataset. [Online].; Telkom
Segmentation of the Left Ventricle of the Heart From University Dataverse 2021. Available from:
Ultrasound Data Using Deep Learning Architectures https://doi.org/10.34820/FK2/QVCP6V.
and Derivative-Based Search Methods. IEEE
Transactions on Image Processing. 2012; 21(3): 968- Competing interests: Authors declare that they
982. have no competing interests .
10. Han Sea. A deep learning framework for supporting
the classification of breast lesions in ultrasound
images. Physics in medicine and biology. 2017; Data and materials availability: All data are
62(19): 7714-7728. available in the main text .
11. Hosain AKMS, Mehedi MHK, Kabir IE. PCONet: A
convolutional neural network architecture to detect
polycystic ovary syndrome (PCOS) from ovarian
ultrasound images. arXiv preprint. 2022 Oct 2.
12. Kaggle. [Online]. Available from:
https://www.kaggle.com/datasets/anaghachoudha
ri/pcos-detection-using-ultrasound-images.
13. Lv Wea. Deep Learning Algorithm for Automated
Detection of Polycystic Ovary Syndrome Using
Scleral Images. Frontiers in endocrinology. 2022 Jan.
27; 12.
14. S. Bharati, Podder P, et al. Diagnosis of Polycystic
Ovary Syndrome Using Machine Learning
Algorithms. 2020 IEEE Region 10 Symposium
(TENSYMP). 2020;: 1486-1489.
15. Srivastava S, Kumar P, et al. Detection of Ovarian
Cyst in Ultrasound Images Using Fine Tuned VGG 16
Deep Learning Network. SN Computer Science. 2020.
16. PyTorch. Documentation for DenseNet201. [Online].
Available from: https://pytorch.org/vision/main
/models/generated/torchvision.models.densenet20
1.html.
17. Steiner A et al. How to train your ViT? Data,
Augmentation, and Regularization in Vision
Transformers. Transactions on Machine Learning
Research;https://doi.org/10.48550/arXiv.2106.102.
18. Huang G et al. Densely Connected Convolutional
Networks. 2017 IEEE Conference on Computer Vision
and Pattern Recognition (CVPR). 2016; 2261-2269.
19. Morid MA, Borjali A, Del Fiol G. A scoping review of
transfer learning research on medical image analysis
using ImageNet. Computers in biology and medicine.
2020; 128: 104115.
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