Gotowe bibliografie tematyczne / Optic cup segmentation

Spis treści

  1. Artykuły w czasopismach
  2. Części książek
  3. Streszczenia konferencji

Gotowa bibliografia na temat „Optic cup segmentation”

Autor: Grafiati
Data publikacji: 2 czerwca 2025
Data aktualizacji: 31 lipca 2025

Utwórz poprawne odniesienie w stylach APA, MLA, Chicago, Harvard i wielu innych

Wybierz rodzaj źródła:

Zobacz listy aktualnych artykułów, książek, rozpraw, streszczeń i innych źródeł naukowych na temat „Optic cup segmentation”.

Przycisk „Dodaj do bibliografii” jest dostępny obok każdej pracy w bibliografii. Użyj go – a my automatycznie utworzymy odniesienie bibliograficzne do wybranej pracy w stylu cytowania, którego potrzebujesz: APA, MLA, Harvard, Chicago, Vancouver itp.

Możesz również pobrać pełny tekst publikacji naukowej w formacie „.pdf” i przeczytać adnotację do pracy online, jeśli odpowiednie parametry są dostępne w metadanych.

Artykuły w czasopismach na temat "Optic cup segmentation"

1

Zhou, Wei, Yugen Yi, Yuan Gao, and Jiangyan Dai. "Optic Disc and Cup Segmentation in Retinal Images for Glaucoma Diagnosis by Locally Statistical Active Contour Model with Structure Prior." Computational and Mathematical Methods in Medicine 2019 (November 20, 2019): 1–16. http://dx.doi.org/10.1155/2019/8973287.

Pełny tekst źródła
Streszczenie:
Accurate optic disc and optic cup segmentation plays an important role for diagnosing glaucoma. However, most existing segmentation approaches suffer from the following limitations. On the one hand, image devices or illumination variations always lead to intensity inhomogeneity in the fundus image. On the other hand, the spatial prior knowledge of optic disc and optic cup, e.g., the optic cup is always contained inside the optic disc region, is ignored. Therefore, the effectiveness of segmentation approaches is greatly reduced. Different from most previous approaches, we present a novel locall
Style APA, Harvard, Vancouver, ISO itp.
2

Rakes, Geethalakshmi, and Vani Rajamanickam. "A Novel Deep Learning Algorithm for Optical Disc Segmentation for Glaucoma Diagnosis." Traitement du Signal 39, no. 1 (2022): 305–11. http://dx.doi.org/10.18280/ts.390132.

Pełny tekst źródła
Streszczenie:
In India, first major cause of blindness is the cataract and the next major cause of blindness is the glaucoma which is approximately 11.9 million per yearly. The Optical Nerve Head (ONH) misalignment is the initial symptom which helps in predicting glaucoma in early stage. The optic cup and optic disc misalignment cause variation in Cup to Disc Ratio (CDR). Accurate segmentation of optic disc and cup is needed in order to calculate CDR properly. Manual segmentation can be automated to improve accuracy. Several deep learning algorithms are proposed to improve segmentation of optic cup and disc
Style APA, Harvard, Vancouver, ISO itp.
3

Jiang, Yun, Falin Wang, Jing Gao, and Simin Cao. "Multi-Path Recurrent U-Net Segmentation of Retinal Fundus Image." Applied Sciences 10, no. 11 (2020): 3777. http://dx.doi.org/10.3390/app10113777.

Pełny tekst źródła
Streszczenie:
Diabetes can induce diseases including diabetic retinopathy, cataracts, glaucoma, etc. The blindness caused by these diseases is irreversible. Early analysis of retinal fundus images, including optic disc and optic cup detection and retinal blood vessel segmentation, can effectively identify these diseases. The existing methods lack sufficient discrimination power for the fundus image and are easily affected by pathological regions. This paper proposes a novel multi-path recurrent U-Net architecture to achieve the segmentation of retinal fundus images. The effectiveness of the proposed network
Style APA, Harvard, Vancouver, ISO itp.
4

Alia Zainudin, Noraina, Ain Nazari, Mohd Marzuki Mustafa, Wan NurShazwani Wan Zakaria, Nor Surayahani Suriani, and Wan Nur Hafsha Wan Kairuddin. "Glaucoma detection of retinal images based on boundary segmentation." Indonesian Journal of Electrical Engineering and Computer Science 18, no. 1 (2020): 377. http://dx.doi.org/10.11591/ijeecs.v18.i1.pp377-384.

Pełny tekst źródła
Streszczenie:
<p>The rapid growth of technology makes it possible to implement in immediate diagnosis for patients using image processing. By using morphological processing and adaptive thresholding method for segmentation of optic disc and optic cup, various sizes of retinal fundus images captured through fundus camera from online databases can be processed. This paper explains the use of color channel separation method for pre-processing to remove noise for better optic disc and optic cup segmentation. Noise removal will improve image quality and in return help to increase segmentation standard. The
Style APA, Harvard, Vancouver, ISO itp.
5

Noraina, Alia Zainudin, Nazari Ain, Marzuki Mustafa Mohd, NurShazwani Wan Zakaria Wan, Surayahani Suriani Nor, and Nur Hafsha Wan Kairuddin Wan. "Glaucoma detection of retinal images based on boundary segmentation." Indonesian Journal of Electrical Engineering and Computer Science (IJEECS) 18, no. 1 (2020): 377–84. https://doi.org/10.11591/ijeecs.v18.i1.pp377-384.

Pełny tekst źródła
Streszczenie:
The rapid growth of technology makes it possible to implement in immediate diagnosis for patients using image processing. By using morphological processing and adaptive thresholding method for segmentation of optic disc and optic cup, various sizes of retinal fundus images captured through fundus camera from online databases can be processed. This paper explains the use of color channel separation method for pre-processing to remove noise for better optic disc and optic cup segmentation. Noise removal will improve image quality and in return help to increase segmentation standard. Then, morpho
Style APA, Harvard, Vancouver, ISO itp.
6

Zhang, Fengming, Shuiwang Li, and Jianzhi Deng. "Unsupervised Domain Adaptation with Shape Constraint and Triple Attention for Joint Optic Disc and Cup Segmentation." Sensors 22, no. 22 (2022): 8748. http://dx.doi.org/10.3390/s22228748.

Pełny tekst źródła
Streszczenie:
Currently, glaucoma has become an important cause of blindness. At present, although glaucoma cannot be cured, early treatment can prevent it from getting worse. A reliable way to detect glaucoma is to segment the optic disc and cup and then measure the cup-to-disc ratio (CDR). Many deep neural network models have been developed to autonomously segment the optic disc and the optic cup to help in diagnosis. However, their performance degrades when subjected to domain shift. While many domain-adaptation methods have been exploited to address this problem, they are apt to produce malformed segmen
Style APA, Harvard, Vancouver, ISO itp.
7

Adi Nugroho, Hanung, Thea Kirana, Vicko Pranowo, and Augustine Herini Tita Hutami. "Optic cup segmentation using adaptive threshold and morphological image processing." Communications in Science and Technology 4, no. 2 (2019): 63–67. http://dx.doi.org/10.21924/cst.4.2.2019.125.

Pełny tekst źródła
Streszczenie:
Glaucoma is a chronic optic neuropathy. It was predicted that people with bilateral blindness caused by glaucoma will increase each year. Hence, computer-aided diagnosis of glaucoma was proposed to assist ophthalmologist to conduct a fast and accurate glaucoma screening. One of the ocular examination in screening is optic nerve examination called disc damage likelihood scale (DDLS). It is important to find the optic disc and the optic cup to determine the narrowest width of the neuroretinal rim when using DDLS. To find the optic cup, this study proposed a segmentation scheme consisting of pre-
Style APA, Harvard, Vancouver, ISO itp.
8

Almazroa, Ahmed, Ritambhar Burman, Kaamran Raahemifar, and Vasudevan Lakshminarayanan. "Optic Disc and Optic Cup Segmentation Methodologies for Glaucoma Image Detection: A Survey." Journal of Ophthalmology 2015 (2015): 1–28. http://dx.doi.org/10.1155/2015/180972.

Pełny tekst źródła
Streszczenie:
Glaucoma is the second leading cause of loss of vision in the world. Examining the head of optic nerve (cup-to-disc ratio) is very important for diagnosing glaucoma and for patient monitoring after diagnosis. Images of optic disc and optic cup are acquired by fundus camera as well as Optical Coherence Tomography. The optic disc and optic cup segmentation techniques are used to isolate the relevant parts of the retinal image and to calculate the cup-to-disc ratio. The main objective of this paper is to review segmentation methodologies and techniques for the disc and cup boundaries which are ut
Style APA, Harvard, Vancouver, ISO itp.
9

Mangipudi, Partha Sarathi, Hari Mohan Pandey, and Ankur Choudhary. "Improved optic disc and cup segmentation in Glaucomatic images using deep learning architecture." Multimedia Tools and Applications 80, no. 20 (2021): 30143–63. http://dx.doi.org/10.1007/s11042-020-10430-6.

Pełny tekst źródła
Streszczenie:
AbstractGlaucoma is an ailment causing permanent vision loss but can be prevented through the early detection. Optic disc to cup ratio is one of the key factors for glaucoma diagnosis. But accurate segmentation of disc and cup is still a challenge. To mitigate this challenge, an effective system for optic disc and cup segmentation using deep learning architecture is presented in this paper. Modified Groundtruth is utilized to train the proposed model. It works as fused segmentation marking by multiple experts that helps in improving the performance of the system. Extensive computer simulations
Style APA, Harvard, Vancouver, ISO itp.
10

Tadisetty, Srikanth, Ranjith Chodavarapu, Ruoming Jin, Robert J. Clements, and Minzhong Yu. "Identifying the Edges of the Optic Cup and the Optic Disc in Glaucoma Patients by Segmentation." Sensors 23, no. 10 (2023): 4668. http://dx.doi.org/10.3390/s23104668.

Pełny tekst źródła
Streszczenie:
With recent advancements in artificial intelligence, fundus diseases can be classified automatically for early diagnosis, and this is an interest of many researchers. The study aims to detect the edges of the optic cup and the optic disc of fundus images taken from glaucoma patients, which has further applications in the analysis of the cup-to-disc ratio (CDR). We apply a modified U-Net model architecture on various fundus datasets and use segmentation metrics to evaluate the model. We apply edge detection and dilation to post-process the segmentation and better visualize the optic cup and opt
Style APA, Harvard, Vancouver, ISO itp.
Więcej źródeł

Części książek na temat "Optic cup segmentation"

1

Cheng, Jun, Jiang Liu, Dacheng Tao, et al. "Superpixel Classification Based Optic Cup Segmentation." In Medical Image Computing and Computer-Assisted Intervention – MICCAI 2013. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-40760-4_53.

Pełny tekst źródła
Style APA, Harvard, Vancouver, ISO itp.
2

Veerasenthilkumar, G., S. Vasuki, and R. Rajkumar. "Optic Disk and Optic Cup Segmentation for Glaucoma Screening." In Advances in Intelligent Systems and Computing. Springer India, 2014. http://dx.doi.org/10.1007/978-81-322-2135-7_77.

Pełny tekst źródła
Style APA, Harvard, Vancouver, ISO itp.
3

Alex David, S., N. Ruth Naveena, S. Ravikumar, and M. J. Carmel Mary Belinda. "Optic disc and optic cup segmentation based on deep learning methods." In Artificial Intelligence, Blockchain, Computing and Security Volume 2. CRC Press, 2023. http://dx.doi.org/10.1201/9781032684994-52.

Pełny tekst źródła
Style APA, Harvard, Vancouver, ISO itp.
4

Feng, Yaowei, Shijie Zhou, Yaoxing Wang, Zhendong Li, and Hao Liu. "Edge-Prior Contrastive Transformer for Optic Cup and Optic Disc Segmentation." In Pattern Recognition and Computer Vision. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-8469-5_35.

Pełny tekst źródła
Style APA, Harvard, Vancouver, ISO itp.
5

Li, Wenyi, and Jun Yao. "Study on Optic Disc and Optic Cup Segmentation Based on SCUNet++." In Communications in Computer and Information Science. Springer Nature Singapore, 2024. https://doi.org/10.1007/978-981-96-0294-0_13.

Pełny tekst źródła
Style APA, Harvard, Vancouver, ISO itp.
6

Thakur, Niharika, and Mamta Juneja. "Comparative Analysis on Optic Cup and Optic Disc Segmentation for Glaucoma Diagnosis." In Proceedings of 3rd International Conference on Advanced Computing, Networking and Informatics. Springer India, 2015. http://dx.doi.org/10.1007/978-81-322-2538-6_23.

Pełny tekst źródła
Style APA, Harvard, Vancouver, ISO itp.
7

Xue, Xiaozhong, Linni Wang, Ayaka Ehiro, Yahui Peng, and Weiwei Du. "Optic Cup Segmentation from Fundus Image Using Swin-Unet." In Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-56388-1_7.

Pełny tekst źródła
Style APA, Harvard, Vancouver, ISO itp.
8

Zhou, Ke, Yufei Zhan, Zhe Si, Yang Liu, and Dongmei Fu. "A Multi-feature Fusion Method for Optic Cup Segmentation." In Lecture Notes in Electrical Engineering. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-6324-6_5.

Pełny tekst źródła
Style APA, Harvard, Vancouver, ISO itp.
9

Sandoval-Cuellar, H. J., M. A. Vázquez Membrillo, G. Alfonso-Francia, J. C. Ortega Pedraza, and S. Tovar-Arriaga. "Optic Disc and Optic Cup Segmentation Using Polar Coordinate and Encoder-Decoder Architecture." In Communications in Computer and Information Science. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-89586-0_9.

Pełny tekst źródła
Style APA, Harvard, Vancouver, ISO itp.
10

Sarhan, Abdullah, Jone Rokne, and Reda Alhajj. "H-OCS: A Hybrid Optic Cup Segmentation of Retinal Images." In Computer Analysis of Images and Patterns. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-89128-2_12.

Pełny tekst źródła
Style APA, Harvard, Vancouver, ISO itp.

Streszczenia konferencji na temat "Optic cup segmentation"

1

Arpacı, Saadet Aytaç, and Songül Varlı. "Segmentation of the Optic Cup." In 2024 9th International Conference on Computer Science and Engineering (UBMK). IEEE, 2024. https://doi.org/10.1109/ubmk63289.2024.10773594.

Pełny tekst źródła
Style APA, Harvard, Vancouver, ISO itp.
2

R, Priyanka, and Lavanya R. "A Hybrid Clustering-based Approach for Segmentation of Optic Disc and Optic Cup." In 2024 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT). IEEE, 2024. http://dx.doi.org/10.1109/conecct62155.2024.10677252.

Pełny tekst źródła
Style APA, Harvard, Vancouver, ISO itp.
3

Shi, Weiya, Can Feng, Tiantian Wang, and Yitao Liang. "Optic Disk and Cup Segmentation Using Dual Branch and Transformer." In 2024 8th International Symposium on Computer Science and Intelligent Control (ISCSIC). IEEE, 2024. https://doi.org/10.1109/iscsic64297.2024.00036.

Pełny tekst źródła
Style APA, Harvard, Vancouver, ISO itp.
4

Preity, Akanksha Jha, Ashish Kumar Bhandari, and Syed Shahnawazuddin. "Joint Optic Nerve Head and Cup Segmentation Based on Deep Residual Network." In 2024 International Conference on Signal Processing and Communications (SPCOM). IEEE, 2024. http://dx.doi.org/10.1109/spcom60851.2024.10631642.

Pełny tekst źródła
Style APA, Harvard, Vancouver, ISO itp.
5

Rantaya, Iga Novinda, Syukron Abu Ishaq Alfarozi, and Hanung Adi Nugroho. "Leveraging Segformer for Precision Segmentation of Optic Cup and Optic Disc in Fundus Imaging for Glaucoma Detection." In 2025 International Conference on Advancement in Data Science, E-learning and Information System (ICADEIS). IEEE, 2025. https://doi.org/10.1109/icadeis65852.2025.10932981.

Pełny tekst źródła
Style APA, Harvard, Vancouver, ISO itp.
6

Wang, Lianyu, Dingwei Fan, Meng Wang, and Daoqiang Zhang. "AISA-DG: Automatic Implicit Style-Augmented Domain Generalization on Optic Disc/Cup Segmentation." In 2024 IEEE International Symposium on Biomedical Imaging (ISBI). IEEE, 2024. http://dx.doi.org/10.1109/isbi56570.2024.10635681.

Pełny tekst źródła
Style APA, Harvard, Vancouver, ISO itp.
7

Inkong-Ngam, Siwakorn, Kreangsak Tamee, and Rabian Wangkeeree. "Automated Optic Disc and Cup Segmentation Using Mask R-CNN for Glaucoma Assessment." In 2025 IEEE International Conference on Cybernetics and Innovations (ICCI). IEEE, 2025. https://doi.org/10.1109/icci64209.2025.10987508.

Pełny tekst źródła
Style APA, Harvard, Vancouver, ISO itp.
8

K J, Tina Brivitha, and Sophia S. "Integrated Deep Learning Framework for Automated Glaucoma Detection, Optic Disc/ Cup Segmentation, and CDR Calculation." In 2025 International Conference on Visual Analytics and Data Visualization (ICVADV). IEEE, 2025. https://doi.org/10.1109/icvadv63329.2025.10961500.

Pełny tekst źródła
Style APA, Harvard, Vancouver, ISO itp.
9

Yu, Jinchen, Yongwei Nie, Fei Qi, Wenxiong Liao, and Hongmin Cai. "FunduSAM: A Specialized Deep Learning Model for Enhanced Optic Disc and Cup Segmentation in Fundus Images." In 2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2024. https://doi.org/10.1109/bibm62325.2024.10822454.

Pełny tekst źródła
Style APA, Harvard, Vancouver, ISO itp.
10

Cho, Sanghyeon, Bogyeong Kang, Keun-Soo Heo, EunJung Jo, and Tae-Eui Kam. "Enhanced Structure Preservation and Multi-View Approach in Unsupervised Domain Adaptation for Optic Disc and Cup Segmentation." In 2024 IEEE International Symposium on Biomedical Imaging (ISBI). IEEE, 2024. http://dx.doi.org/10.1109/isbi56570.2024.10635127.

Pełny tekst źródła
Style APA, Harvard, Vancouver, ISO itp.
Możesz być także zainteresowany rozszerzonymi bibliografiami na temat „Optic cup segmentation” dla poszczególnych typów źródeł:
Artykuły w czasopismach
Oferujemy zniżki na wszystkie plany premium dla autorów, których prace zostały uwzględnione w tematycznych zestawieniach literatury. Skontaktuj się z nami, aby uzyskać unikalny kod promocyjny!

Do bibliografii