Search Results for author:
Found 16 papers, 1 papers with code
A metric to compare the anatomy variation between image time series
A method to untangle and quantify the path and inter-subject anatomy(shape) difference between the TS is presented in this paper.
Sub-cortical structure segmentation database for young population
Segmentation of sub-cortical structures from MRI scans is of interest in many neurological diagnosis.
A Diffeomorphic Aging Model for Adult Human Brain from Cross-Sectional Data
We propose a method to develop an aging model for a given population, in the absence of longitudinal data, by using images from different subjects at different time points, the so-called cross-sectional data.
A Clinically Inspired Approach for Melanoma classification
This is then incorporated in a CAD system design for melanoma detection.
Self-Supervised Learning for Segmentation
A siamese convolutional neural network (CNN) is used to classify a given pair of kidney sections from CT volumes as being kidneys of the same or different sides.
A method for large diffeomorphic registration via broken geodesics
Anatomical variabilities seen in longitudinal data or inter-subject data is usually described by the underlying deformation, captured by non-rigid registration of these images.
Explainable Disease Classification via weakly-supervised segmentation
Results of testing on on a large public dataset show that with just a third of images with roughly segmented fluid filled regions, the classification accuracy is on par with state of the art methods while providing a good explanation in the form of anatomically accurate heatmap /region of interest.
Image Segmentation Using Hybrid Representations
This work explores a hybrid approach to segmentation as an alternative to a purely data-driven approach.
FPD-M-net: Fingerprint Image Denoising and Inpainting Using M-Net Based Convolutional Neural Networks
Our architecture is based on the M-net with a change: structure similarity loss function, used for better extraction of the fingerprint from the noisy background.
A deep learning framework for segmentation of retinal layers from OCT images
Segmentation of retinal layers from Optical Coherence Tomography (OCT) volumes is a fundamental problem for any computer aided diagnostic algorithm development.
A Generalized Motion Pattern and FCN based approach for retinal fluid detection and segmentation
SD-OCT is a non-invasive cross-sectional imaging modality used for diagnosis of macular defects.
To Learn or Not to Learn Features for Deformable Registration?
Feature-based registration has been popular with a variety of features ranging from voxel intensity to Self-Similarity Context (SSC).
Segmentation of retinal cysts from Optical Coherence Tomography volumes via selective enhancement
The robustness of the algorithm was examined by cross-validation on the DME and AEI (private) datasets and a mean DC values obtained were 0. 69 and 0. 79, respectively.
Domain knowledge assisted cyst segmentation in OCT retinal images
OCT is one such modality which has great importance in the context of analysis of cystoid structures in subretinal layers.
Cardiac Motion Analysis by Temporal Flow Graphs
The paper proposes a new methodology for cardiac motion analysis based on the temporal behaviour of points of interest on the myocardium.
Drishti-GS: Retinal image dataset for optic nerve head(ONH) segmentation
Optic nerve head (ONH) segmentation problem has been of interest for automated glaucoma assessment.
