Journal ArticleDOI
Automatic Optic Disc Boundary Extraction Based on Saliency Object Detection and Modified Local Intensity Clustering Model in Retinal Images
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This article is published in IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences.The article was published on 2017-09-01. It has received 13 citations till now. The article focuses on the topics: Object detection & Optic disc.read more
Citations
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Journal ArticleDOI
Optic Disc and Cup Segmentation in Retinal Images for Glaucoma Diagnosis by Locally Statistical Active Contour Model with Structure Prior.
TL;DR: A novel locally statistical active contour model with the structure prior (LSACM-SP) approach to jointly and robustly segment the optic disc and optic cup structures in the presence of intensity inhomogeneity is presented.
Journal ArticleDOI
Automated segmentation of optic disc and optic cup for glaucoma assessment using improved UNET++ architecture
TL;DR: A novel approach is developed for the identification of glaucoma using a segmentation based approach on the optic disc and optic cup using a custom UNET++ model, able to achieve state-of-art results for Intersection over Union (IOU) scores and improvement in training time.
Journal ArticleDOI
Accurate and Efficient Segmentation of Optic Disc and Optic Cup in Retinal Images Integrating Multi-View Information
TL;DR: The main contributions are to introduce the Locally Statistical Active Contour Model (LSACM) to address the commonly occurred intensity inhomogeneity phenomenon caused by imperfection of image devices or illumination variations and to integrate the local image probability information around the point of interest from a multi-dimensional feature space into the model.
Journal ArticleDOI
Automatic optic disc detection using low-rank representation based semi-supervised extreme learning machine
TL;DR: A novel approach named low-rank representation based semi-supervised extreme learning machine (LRR-SSELM) is proposed for automated optic disc detection and the experimental results indicate the advantages and effectiveness of the proposed approach.
Journal ArticleDOI
Automatic Optic Disc Segmentation Based on Modified Local Image Fitting Model with Shape Prior Information.
TL;DR: An approach for segmenting OD boundary without manpower named full-automatic double boundary extraction is designed and a modified LIF approach is presented by incorporating the shape prior information into LIF to handle unreliable information generated by intensity in abnormal retinal images caused by diseases.
References
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Journal ArticleDOI
A Level Set Method for Image Segmentation in the Presence of Intensity Inhomogeneities With Application to MRI
TL;DR: A novel region-based method for image segmentation, which is able to simultaneously segment the image and estimate the bias field, and the estimated bias field can be used for intensity inhomogeneity correction (or bias correction).
Proceedings ArticleDOI
the DIARETDB1 diabetic retinopathy database and evaluation protocol
Tomi Kauppi,V. Kalesnykiene,Joni-Kristian Kamarainen,Lasse Lensu,Iiris Sorri,A. Raninen,Raimo Voutilainen,Hannu Uusitalo,Heikki Kälviäinen,Juhani Pietilä +9 more
TL;DR: With the proposed database and protocol, it is possible to compare different algorithms, and correspondingly, analyse their maturity for technology transfer from the research laboratories to the medical practice.
Journal ArticleDOI
Fast and robust optic disc detection using pyramidal decomposition and Hausdorff-based template matching
TL;DR: Reports on the design and test of an image processing algorithm for the localization of the optic disk in low-resolution (about 20 /spl mu//pixel) color fundus images and a confidence level is associated to the final detection that indicates the "level of difficulty" the detector has to identify the OD position and shape.
Journal ArticleDOI
Optic Disk and Cup Segmentation From Monocular Color Retinal Images for Glaucoma Assessment
TL;DR: An automatic OD parameterization technique based on segmented OD and cup regions obtained from monocular retinal images and a novel cup segmentation method which is based on anatomical evidence such as vessel bends at the cup boundary, considered relevant by glaucoma experts are presented.
Journal ArticleDOI
A novel automatic image processing algorithm for detection of hard exudates based on retinal image analysis.
TL;DR: The proposed algorithm is based on Fisher's linear discriminant analysis and makes use of colour information to perform the classification of retinal exudates and achieved an image-based classification accuracy of 100%