15 citations · 47 across the 17 of their papers we have counts for
20 papers
Evidence-Driven Differential Diagnosis of Malignant Melanoma
Naren Akash, Anirudh Kaushik, Jayanthi Sivaswamy
We present a modular and multi-level framework for the differential diagnosis of malignant melanoma. Our framework integrates contextual information and evidence at the lesion, pat…
CheXtriev: Anatomy-Centered Representation for Case-Based Retrieval of Chest Radiographs
Naren Akash, Arihanth Tadanki, Jayanthi Sivaswamy
We present CheXtriev, a graph-based, anatomy-aware framework for chest radiograph retrieval. Unlike prior methods focussed on global features, our method leverages graph transforme…
Understanding Brain Aging Across Populations: A Comprehensive Framework for Structural Analysis
Alphin J Thottupattu, Jayanthi Sivaswamy, Bharath Holla +1
Understanding distinct neurological aging patterns across various populations is vital in the context of a globally aging populace. This study seeks to unravel the structural varia…
Nerve Block Target Localization and Needle Guidance for Autonomous Robotic Ultrasound Guided Regional Anesthesia
Abhishek Tyagi, Abhay Tyagi, Manpreet Kaur +4
Visual servoing for the development of autonomous robotic systems capable of administering UltraSound (US) guided regional anesthesia requires real-time segmentation of nerves, nee…
A metric to compare the anatomy variation between image time series
Alphin J Thottupattu, Jayanthi Sivaswamy
Biological processes like growth, aging, and disease progression are generally studied with follow-up scans taken at different time points, i.e., with image time series (TS) based…
Sub-cortical structure segmentation database for young population
Jayanthi Sivaswamy, Alphin J Thottupattu, Mythri V +3
Segmentation of sub-cortical structures from MRI scans is of interest in many neurological diagnosis. Since this is a laborious task machine learning and specifically deep learning…
A Diffeomorphic Aging Model for Adult Human Brain from Cross-Sectional Data
Alphin J Thottupattu, Jayanthi Sivaswamy, Venkateswaran P. Krishnan
Normative aging trends of the brain can serve as an important reference in the assessment of neurological structural disorders. Such models are typically developed from longitudina…
A Clinically Inspired Approach for Melanoma classification
Prathyusha Akundi, Soumyasis Gun, Jayanthi Sivaswamy
Melanoma is a leading cause of deaths due to skin cancer deaths and hence, early and effective diagnosis of melanoma is of interest. Current approaches for automated diagnosis of m…
Self-Supervised Learning for Segmentation
Abhinav Dhere, Jayanthi Sivaswamy
Self-supervised learning is emerging as an effective substitute for transfer learning from large datasets. In this work, we use kidney segmentation to explore this idea. The anatom…
A method for large diffeomorphic registration via broken geodesics
Alphin J. Thottupattu, Jayanthi Sivaswamy, Venkateswaran P. Krishnan
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. Sta…
Explainable Disease Classification via weakly-supervised segmentation
Aniket Joshi, Gaurav Mishra, Jayanthi Sivaswamy
Deep learning based approaches to Computer Aided Diagnosis (CAD) typically pose the problem as an image classification (Normal or Abnormal) problem. These systems achieve high to v…
Image Segmentation Using Hybrid Representations
Alakh Desai, Ruchi Chauhan, Jayanthi Sivaswamy
This work explores a hybrid approach to segmentation as an alternative to a purely data-driven approach. We introduce an end-to-end U-Net based network called DU-Net, which uses ad…
FPD-M-net: Fingerprint Image Denoising and Inpainting Using M-Net Based Convolutional Neural Networks
Sukesh Adiga, Jayanthi Sivaswamy
Fingerprint is a common biometric used for authentication and verification of an individual. These images are degraded when fingers are wet, dirty, dry or wounded and due to the fa…
A Deep Learning based Joint Segmentation and Classification Framework for Glaucoma Assesment in Retinal Color Fundus Images
Arunava Chakravarty, Jayanthi Sivswamy
Automated Computer Aided diagnostic tools can be used for the early detection of glaucoma to prevent irreversible vision loss. In this work, we present a Multi-task Convolutional N…
A deep learning framework for segmentation of retinal layers from OCT images
Karthik Gopinath, Samrudhdhi B Rangrej, Jayanthi Sivaswamy
Segmentation of retinal layers from Optical Coherence Tomography (OCT) volumes is a fundamental problem for any computer aided diagnostic algorithm development. This requires prepr…
A Generalized Motion Pattern and FCN based approach for retinal fluid detection and segmentation
Shivin Yadav, Karthik Gopinath, Jayanthi Sivaswamy
SD-OCT is a non-invasive cross-sectional imaging modality used for diagnosis of macular defects. Efficient detection and segmentation of the abnormalities seen as biomarkers in OCT…
To Learn or Not to Learn Features for Deformable Registration?
Aabhas Majumdar, Raghav Mehta, Jayanthi Sivaswamy
Feature-based registration has been popular with a variety of features ranging from voxel intensity to Self-Similarity Context (SSC). In this paper, we examine the question on how…
Segmentation of retinal cysts from Optical Coherence Tomography volumes via selective enhancement
Karthik Gopinath, Jayanthi Sivaswamy
Automated and accurate segmentation of cystoid structures in Optical Coherence Tomography (OCT) is of interest in the early detection of retinal diseases. It is, however, a challen…
Domain knowledge assisted cyst segmentation in OCT retinal images
Karthik Gopinath, Jayanthi Sivaswamy
3D imaging modalities are becoming increasingly popular and relevant in retinal imaging owing to their effectiveness in highlighting structures in sub-retinal layers. OCT is one su…
Cardiac Motion Analysis by Temporal Flow Graphs
V S R Veeravasarapu, Jayanthi Sivaswamy, Vishanji Karani
Cardiac motion analysis from B-mode ultrasound sequence is a key task in assessing the health of the heart. The paper proposes a new methodology for cardiac motion analysis based o…