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Drishti-GS: Retinal image dataset for optic nerve head(ONH) segmentation
- J. Sivaswamy, S. R. Krishnadas, Gopal Datt Joshi, Madhulika Jain, A. U. S. Tabish
- Computer Science, MedicineIEEE 11th International Symposium on Biomedical…
- 1 April 2014
A comprehensive dataset of retinal images which include both normal and glaucomatous eyes and manual segmentations from multiple human experts is presented and area and boundary-based evaluation measures are presented to evaluate a method on various aspects relevant to the problem ofglaucoma assessment.
Optic Disk and Cup Segmentation From Monocular Color Retinal Images for Glaucoma Assessment
- Gopal Datt Joshi, J. Sivaswamy, S. R. Krishnadas
- MedicineIEEE Transactions on Medical Imaging
- 2 May 2011
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.
A Comprehensive Retinal Image Dataset for the Assessment of Glaucoma from the Optic Nerve Head Analysis
A comprehensive dataset of retinal images of both normal and glaucomatous eyes with manual segmentations from multiple human experts with expert opinion is presented to aid benchmarking of new methods.
Hexagonal Image Processing: A Practical Approach
This paper presents a comparison of the practical aspects of hexagonal image processing on square and hexagonal grids and discusses the proposed HIP framework.
M-net: A Convolutional Neural Network for deep brain structure segmentation
- Raghav Mehta, J. Sivaswamy
- Computer ScienceIEEE 14th International Symposium on Biomedical…
- 1 April 2017
The M-net is proposed, an end-to-end trainable Convolutional Neural Network architecture for segmenting deep (human) brain structures from Magnetic Resonance Images (MRI) and is at least 3 times faster than other methods in segmenting a new volume which is attractive for clinical use.
Automatic assessment of macular edema from color retinal images
A two-stage methodology for the detection and classification of DME severity from color fundus images is proposed and the effectiveness of the proposed solution is established.
FPD-M-net: Fingerprint Image Denoising and Inpainting Using M-Net Based Convolutional Neural Networks
This work proposes an end-to-end trainable Convolutional Neural Network based architecture called FPD-M-net, based on the M-net with a change: structure similarity loss function, used for better extraction of the fingerprint from the noisy background.
Optic disk and cup boundary detection using regional information
- Gopal Datt Joshi, J. Sivaswamy, Kundun Karan, S. R. Krishnadas
- MedicineIEEE International Symposium on Biomedical…
- 14 April 2010
The shape deformation within the optic disk (OD) is an important indicator for the detection of glaucoma. In this paper, relevant disk parameters are estimated using the OD and cup boundaries. A…
BrainSegNet: a convolutional neural network architecture for automated segmentation of human brain structures
The consistently good performance of the proposed method across datasets and no requirement for registration make it attractive for many applications where reduced computational time is necessary.
Colour Retinal Image Enhancement Based on Domain Knowledge
- Gopal Datt Joshi, J. Sivaswamy
- Computer ScienceSixth Indian Conference on Computer Vision…
- 16 December 2008
The knowledge of the imaging geometry is used and an enhancement method for colour retinal images is proposed, with a focus on contrast improvement with no introduction of artifacts, to show marked improvement over existing methods.