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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

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https://web.archive.org/web/20200911125149/https://arxiv.org/pdf/1812.07101v2.pdf

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2019 pre-print arXiv:1812.07101v2 fatcat:4mktl7fndbazzg3ptg55fhpqbu

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2018 pre-print
arXiv:1812.07101v1 fatcat:ov6knmw5zzaw5iq76w4sg53mqe
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
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Citation

Sourya Sengupta, Amitojdeep Singh, Henry A.Leopold, Tanmay Gulati, Vasudevan Lakshminarayanan. "Application of Deep Learning in Fundus Image Processing for Ophthalmic Diagnosis – A Review." arXiv (2019)

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

Xin Yi, Ekta Walia, Paul Babyn
2019 arXiv   pre-print

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https://web.archive.org/web/20200904123537/https://arxiv.org/pdf/1809.07294v3.pdf

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2019 pre-print
arXiv:1809.07294v2 fatcat:vaxx7tznundzrgkvghzsbtqb7q
2018 pre-print
arXiv:1809.07294v1 fatcat:44obq3fh3bgondkbgzsnpptxoy
2019 accepted
arXiv:1809.07294v4 fatcat:tczvhzb3j5h6nlsqijhpracy6u
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
Multiple Versions
Citation

Xin Yi, Ekta Walia, Paul Babyn. "Generative Adversarial Network in Medical Imaging: A Review." arXiv (2019)

A Systematic Review of Deep Learning Methods Applied to Ocular Images

Oscar Julian Perdomo Charry, Fabio Augusto González Osorio
2019 Ciencia e Ingeniería Neogranadina  

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https://web.archive.org/web/20201105111613/https://revistas.unimilitar.edu.co/index.php/rcin/article/download/4242/4078

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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
DOAJ SciELO
Citation

Oscar Julian Perdomo Charry, Fabio Augusto González Osorio. "A Systematic Review of Deep Learning Methods Applied to Ocular Images." Ciencia e Ingeniería Neogranadina 30.1 (2019) 9-26

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

Minhaj Nur Alam, David Le, Xincheng Yao
2021 Quantitative Imaging in Medicine and Surgery  

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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
Open Access
Citation

Minhaj Nur Alam, David Le, Xincheng Yao. "Differential artery-vein analysis in quantitative retinal imaging: a review." Quantitative Imaging in Medicine and Surgery 11.3 (2021) 1102-1119

A narrative review of glaucoma screening from fundus images

Xingxing Cao, Xu Sun, Shuai Yan, Yanwu Xu
2021 Annals of Eye Science  

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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
Open Access
Citation

Xingxing Cao, Xu Sun, Shuai Yan, Yanwu Xu. "A narrative review of glaucoma screening from fundus images." Annals of Eye Science (2021) 0-0

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

Maximilian E. Tschuchnig, Michael Gadermayr
2021 arXiv   pre-print

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https://web.archive.org/web/20210831141952/https://arxiv.org/pdf/2108.11986v1.pdf

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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
Open Access
Citation

Maximilian E. Tschuchnig, Michael Gadermayr. "Anomaly Detection in Medical Imaging – A Mini Review." arXiv (2021)

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  

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https://web.archive.org/web/20220520175148/https://www.ijraset.com/best-journal/diabetic-retinopathy-disease-classification-using-retina-images-a-review

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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
Open Access
Citation

Syed Efath Hamid Andrab, Ankur Gupta. "Diabetic Retinopathy Disease Classification Using Retina Images: A Review." International Journal for Research in Applied Science and Engineering Technology 10.5 (2022) 1452-1458

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  

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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
Open Access
Citation

Lei Cai, Jingyang Gao, Di Zhao. "A review of the application of deep learning in medical image classification and segmentation." Annals of Translational Medicine 8.11 (2020) 713-713

Medical hyperspectral imaging: a review

Guolan Lu, Baowei Fei
2014 Journal of Biomedical Optics  

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https://web.archive.org/web/20181030054029/https://www.spiedigitallibrary.org/journals/Journal-of-Biomedical-Optics/volume-19/issue-1/010901/Medical-hyperspectral-imaging-a-review/10.1117/1.JBO.19.1.010901.pdf

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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
DOAJ
Citation

Guolan Lu, Baowei Fei. "Medical hyperspectral imaging: a review." Journal of Biomedical Optics 19.1 (2014) 010901

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)  

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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
DOAJ OJS
Citation

Mohammed Enamul Hoque, Kuryati Kipli. "Deep Learning in Retinal Image Segmentation and Feature Extraction: A Review." International Journal of Online and Biomedical Engineering (iJOE) 17.14 (2021) 103-118

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  

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https://web.archive.org/web/20190503094225/https://link.springer.com/content/pdf/10.1007%2Fs40123-018-0153-7.pdf

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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
DOAJ
Citation

Beau J. Fenner, Raymond L. M. Wong, Wai-Ching Lam, Gavin S. W. Tan, Gemmy C. M. Cheung. "Advances in Retinal Imaging and Applications in Diabetic Retinopathy Screening: A Review." Ophthalmology and Therapy 7.2 (2018) 333-346

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

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https://web.archive.org/web/20201114093404/https://arxiv.org/ftp/arxiv/papers/2004/2004.13175.pdf

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2020 pre-print arXiv:2004.13175v4 fatcat:wilsams2c5fclg4zdh5t3ir5ke

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2020 pre-print
arXiv:2004.13175v1 fatcat:tmme5mkwk5gtbpq3jym2ksnygm
2020 pre-print
arXiv:2004.13175v2 fatcat:rm4jnwndbnhurghqy22vof6ypy
2020 pre-print
arXiv:2004.13175v3 fatcat:6b5ahoj6avba7i4gmz4fws425u
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
Multiple Versions
Citation

Mohammad Amin Morid, Alireza Borjali, Guilherme Del Fiol. "A scoping review of transfer learning research on medical image analysis using ImageNet." arXiv (2020)

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  

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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
DOAJ
Citation

Gilbert Lim, Valentina Bellemo, Yuchen Xie, Xin Q. Lee, Michelle Y. T. Yip, Daniel S. W. Ting. "Different fundus imaging modalities and technical factors in AI screening for diabetic retinopathy: a review." Eye and Vision 7.1 (2020) 21

Techniques of Glaucoma Detection From Color Fundus Images: A Review

Malaya Kumar Nath, Samarendra Dandapat
2012 International Journal of Image Graphics and Signal Processing  

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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
Open Access
Citation

Malaya Kumar Nath, Samarendra Dandapat. "Techniques of Glaucoma Detection From Color Fundus Images: A Review." International Journal of Image Graphics and Signal Processing 4.9 (2012) 44-51

Deep learning in photoacoustic imaging: a review

Handi Deng, Hui Qiao, Qionghai Dai, Cheng Ma
2021 Journal of Biomedical Optics  

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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
DOAJ
Citation

Handi Deng, Hui Qiao, Qionghai Dai, Cheng Ma. "Deep learning in photoacoustic imaging: a review." Journal of Biomedical Optics 26.04 (2021)

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