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Application of Deep Learning in Fundus Image Processing for Ophthalmic Diagnosis – A Review [article]

Sourya Sengupta, Amitojdeep Singh, Henry A.Leopold, Tanmay Gulati, Vasudevan Lakshminarayanan
2019 arXiv   pre-print
An overview of the applications of deep learning in ophthalmic diagnosis using retinal fundus images is presented.  ...  Applications of deep learning for segmentation of optic disk, blood vessels and retinal layer as well as detection of lesions are reviewed.  ...  Discussion This review addressed different applications of deep learning methodologies in ophthalmic diagnosis.  ... 
arXiv:1812.07101v3 fatcat:weoh4wnw4ngy5mmq7vwgr2p77e

Generative Adversarial Network in Medical Imaging: A Review [article]

Xin Yi, Ekta Walia, Paul Babyn
2019 arXiv   pre-print
Based on our observations, this trend will continue and we therefore conducted a review of recent advances in medical imaging using the adversarial training scheme with the hope of benefiting researchers  ...  These properties have attracted researchers in the medical imaging community, and we have seen rapid adoption in many traditional and novel applications, such as image reconstruction, segmentation, detection  ...  Introduction With the resurgence of deep learning in computer vision starting from 2012 (Krizhevsky et al., 2012) , the adoption of deep learning methods in medical imaging has increased dramatically.  ... 
arXiv:1809.07294v3 fatcat:5j5i6shlcvbbjm74ceidzg6rc4

A Systematic Review of Deep Learning Methods Applied to Ocular Images

Oscar Julian Perdomo Charry, Fabio Augusto González Osorio
2019 Ciencia e Ingeniería Neogranadina  
In ophthalmology, deep learning methods have primarily been applied to eye fundus images and optical coherence tomography.  ...  This review provides an overview of the state-of-the-art deep learning methods used in ophthalmic images, databases and potential challenges for ocular diagnosis  ...  Discussion This review reports the deep learning state-of-theart works applied to EFIs and OCT for ocular diagnosis as presented in Tables 2 and 3 .  ... 
doi:10.18359/rcin.4242 fatcat:hliqdxp7wndgzcrronn45u7wkm

Differential artery-vein analysis in quantitative retinal imaging: a review

Minhaj Nur Alam, David Le, Xincheng Yao
2021 Quantitative Imaging in Medicine and Surgery  
In this article, we provide a brief summary of technical rationales and clinical applications of differential AV analysis in fundus photography, optical coherence tomography (OCT), and OCT angiography  ...  Therefore, differential artery-vein (AV) analysis can improve the performance of quantitative retinal imaging.  ...  The special issue "Advanced Optical Imaging in Biomedicine" was commissioned by the editorial office without any funding or sponsorship. MNA and XY have a pending patent US2020/022774.  ... 
doi:10.21037/qims-20-557 pmid:33654680 pmcid:PMC7829162 fatcat:wor4txx5yzelza3zg3np57ynwa

A narrative review of glaucoma screening from fundus images

Xingxing Cao, Xu Sun, Shuai Yan, Yanwu Xu
2021 Annals of Eye Science  
The objective of the paper is to provide a general view for automatic cup to disc ratio (CDR) assessment in fundus images.  ...  The key for automatic calculation of vertical CDR in fundus images is the segmentation of optic cup (OC) and optic disc (OD).  ...  Acknowledgments Funding: This work was partially supported by the National Natural Science Foundation of China under Grant No. 61772118.  ... 
doi:10.21037/aes-2020-lto-005 fatcat:2zethzqbg5fs5gcvtgobxzcwki

Anomaly Detection in Medical Imaging – A Mini Review [article]

Maximilian E. Tschuchnig, Michael Gadermayr
2021 arXiv   pre-print
This paper uses a semi-exhaustive literature review of relevant anomaly detection papers in medical imaging to cluster into applications, highlight important results, establish lessons learned and give  ...  The increasing digitization of medical imaging enables machine learning based improvements in detecting, visualizing and segmenting lesions, easing the workload for medical experts.  ...  This however was not always the case [22] but there are still doubts in the clinical applicability of deep learning based anomaly detection methods.  ... 
arXiv:2108.11986v1 fatcat:lzffrlo7ovfppiejztkafzlpyq

Diabetic Retinopathy Disease Classification Using Retina Images: A Review

Syed Efath Hamid Andrab, Ankur Gupta
2022 International Journal for Research in Applied Science and Engineering Technology  
Deep learning has recently been one of the most popular strategies for improving experience in a range of fields, particularly medical image analysis and classifications.  ...  In medical image analysis, convolutional neural networks are becoming increasingly extensively employed as a deep learning approach, and they are quite successful.  ...  The publically accessible fundus DR datasets have been provided, and deep-learning methodologies have been briefly discussed.  ... 
doi:10.22214/ijraset.2022.42432 fatcat:pvkoicircfbsvkddlswkvpdami

A review of the application of deep learning in medical image classification and segmentation

Lei Cai, Jingyang Gao, Di Zhao
2020 Annals of Translational Medicine  
This review introduces the application of intelligent imaging and deep learning in the field of big data analysis and early diagnosis of diseases, combining the latest research progress of big data analysis  ...  This is an issue of great concern to medical and computer researchers, and intelligent imaging and deep learning provide a good answer.  ...  Figure 2 2 Deep learning application in medical image analysis.  ... 
doi:10.21037/atm.2020.02.44 pmid:32617333 pmcid:PMC7327346 fatcat:bywo4riijzemnlu6nilxzdumwu

Medical hyperspectral imaging: a review

Guolan Lu, Baowei Fei
2014 Journal of Biomedical Optics  
This review paper presents an overview of the literature on medical hyperspectral imaging technology and its applications.  ...  Hyperspectral imaging (HSI) is an emerging imaging modality for medical applications, especially in disease diagnosis and image-guided surgery.  ...  Acknowledgments This research is supported in part by National Institute of Health grants (R01CA156775 and R21CA176684), Georgia Research Alliance Distinguished Scientists Award, Emory SPORE in Head and  ... 
doi:10.1117/1.jbo.19.1.010901 pmid:24441941 pmcid:PMC3895860 fatcat:oqkqz2l2d5bala25xqbezlaeri

Deep Learning in Retinal Image Segmentation and Feature Extraction: A Review

Mohammed Enamul Hoque, Kuryati Kipli
2021 International Journal of Online and Biomedical Engineering (iJOE)  
In this review, the recent advances of DL technologies in retinal image segmentation and feature extraction are extensively discussed.  ...  As the morphological retinal image datasets can be analyzed in an expansive and non-invasive way, AI more precisely Deep Learning (DL) methods are facilitating in developing intelligent retinal image analysis  ...  The authors would like to declare that there is no conflict of interest regarding the publication of this paper.  ... 
doi:10.3991/ijoe.v17i14.24819 fatcat:3eeytz33xve6lgyawa6am5w5ly

Advances in Retinal Imaging and Applications in Diabetic Retinopathy Screening: A Review

Beau J. Fenner, Raymond L. M. Wong, Wai-Ching Lam, Gavin S. W. Tan, Gemmy C. M. Cheung
2018 Ophthalmology and Therapy  
Here we review current trends in imaging for DR screening and emerging technologies that show potential for improving upon current screening approaches.  ...  large patient cohorts in a rapid and sensitive manner while minimizing inappropriate referrals to retina specialists.  ...  Ophthalmol Ther (2018) 7:333–346 https://doi.org/10.1007/s40123-018-0153-7 REVIEW Advances in Retinal Imaging and Applications in Diabetic Retinopathy Screening: A Review Beau J. Fenner .  ... 
doi:10.1007/s40123-018-0153-7 pmid:30415454 pmcid:PMC6258577 fatcat:5nxdlalenvhexl4bvvigd2p3tq

A scoping review of transfer learning research on medical image analysis using ImageNet [article]

Mohammad Amin Morid, Alireza Borjali, Guilherme Del Fiol
2020 arXiv   pre-print
We aimed to conduct a scoping review to identify these studies and summarize their characteristics in terms of the problem description, input, methodology, and outcome.  ...  VGGNet was the most common for fundus (42%) and optical coherence tomography images (50%).  ...  Since then, CNN has become a popular machine learning approach for various applications including medical image analysis.  ... 
arXiv:2004.13175v5 fatcat:wqghyqq4wfgpnpatvftty4vzx4

Different fundus imaging modalities and technical factors in AI screening for diabetic retinopathy: a review

Gilbert Lim, Valentina Bellemo, Yuchen Xie, Xin Q. Lee, Michelle Y. T. Yip, Daniel S. W. Ting
2020 Eye and Vision  
In the ophthalmology field, it was demonstrated that deep learning tools for diabetic retinopathy show clinically acceptable diagnostic performance when using colour retinal fundus images.  ...  The advent of artificial intelligence, and in particular deep learning techniques, has however raised the possibility of widespread automated screening.  ...  Acknowledgements Not applicable.  ... 
doi:10.1186/s40662-020-00182-7 pmid:32313813 pmcid:PMC7155252 fatcat:4ayiqdqb6ff5hfiiicypmuyqoa

Techniques of Glaucoma Detection From Color Fundus Images: A Review

Malaya Kumar Nath, Samarendra Dandapat
2012 International Journal of Image Graphics and Signal Processing  
Diagnosis of glaucoma is based on measurement of intraocular pressure by tonometry, visual field examination by perimetry and measurement of cup area to disc area ratio from the color fundus images.  ...  Glaucoma is a generic name for a group of diseases which causes progressive optic neuropathy and vision loss due to degeneration of the optic nerves.  ...  The fundus images are in JPEG format with a resolution of 560 × 720. This method provides a classification rate of 90%, sensitivity 100%, specificity 80% and positive predictive value of 90.9%.  ... 
doi:10.5815/ijigsp.2012.09.07 fatcat:hmtwtglhnzekfadxsmktzypcte

Deep learning in photoacoustic imaging: a review

Handi Deng, Hui Qiao, Qionghai Dai, Cheng Ma
2021 Journal of Biomedical Optics  
In recent years, deep learning (DL) has shown outstanding performance when implemented in PAI, with applications in image reconstruction, quantification, and understanding.  ...  Papers published before November 2020 in the area of applying DL in PAI were reviewed.  ...  The authors would like to thank Youwei Bao and Xiangxiu Zhang for assistance with figure copyright application.  ... 
doi:10.1117/1.jbo.26.4.040901 pmid:33837678 pmcid:PMC8033250 fatcat:uwutps2wfbfztfo6bvbv6g5f6y
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