47 citations · 142 across the 48 of their papers we have counts for
53 papers
SHFormer: Dynamic Spectral Filtering Convolutional Neural Network and High-pass Kernel Generation Transformer for Adaptive MRI Reconstruction
Sriprabha Ramanarayanan, Rahul G. S., Mohammad Al Fahim +3
Attention Mechanism (AM) selectively focuses on essential information for imaging tasks and captures relationships between distant pixel neighborhoods to compute feature representa…
Align-cDAE: Alzheimer's Disease Progression Modeling with Attention-Aligned Conditional Diffusion Auto-Encoder
Ayantika Das, Keerthi Ram, Mohanasankar Sivaprakasam
Generative AI framework-based modeling and prediction of longitudinal human brain images offer an efficient mechanism to track neurodegenerative progression, essential for the asse…
KDPhys: An Attention Guided 3D to 2D Knowledge Distillation for Real-time Video-Based Physiological Measurement
Nicky Nirlipta Sahoo, VS Sachidanand, Matcha Naga Gayathri +4
Camera-based physiological monitoring, such as remote photoplethysmography (rPPG), captures subtle variations in skin optical properties caused by pulsatile blood volume changes us…
CytoCLIP: Learning Cytoarchitectural Characteristics in Developing Human Brain Using Contrastive Language Image Pre-Training
Pralaypati Ta, Sriram Venkatesaperumal, Keerthi Ram +1
The functions of different regions of the human brain are closely linked to their distinct cytoarchitecture, which is defined by the spatial arrangement and morphology of the cells…
AD-DAE: Alzheimer's Disease Progression Modeling with Unpaired Longitudinal MRI using Diffusion Auto-Encoders
Ayantika Das, Arunima Sarkar, Keerthi Ram +1
Generative modeling frameworks have emerged as an effective approach to capture high-dimensional image distributions from large datasets without requiring domain-specific knowledge…
Recovering Diagnostic Value: Super-Resolution-Aided Echocardiographic Classification in Resource-Constrained Imaging
Krishan Agyakari Raja Babu, Om Prabhu, Annu +1
Automated cardiac interpretation in resource-constrained settings (RCS) is often hindered by poor-quality echocardiographic imaging, limiting the effectiveness of downstream diagno…
PosDiffAE: Position-aware Diffusion Auto-encoder For High-Resolution Brain Tissue Classification Incorporating Artifact Restoration
Ayantika Das, Moitreya Chaudhuri, Koushik Bhat +3
Denoising diffusion models produce high-fidelity image samples by capturing the image distribution in a progressive manner while initializing with a simple distribution and compoun…
Optimizing VO2max Prediction in Gamified Cardiac Assessment: Leveraging Effective Feature Selection and Refined Protocols for Robust Models
Vaishnavi C K, Sricharan Vijayarangan, Sri Gayathri G +4
VO2max is a critical indicator of cardiopulmonary fitness, reflecting the maximum amount of oxygen the body can utilize during intense exercise. Accurately measuring VO2max is esse…
Entity-Augmented Neuroscience Knowledge Retrieval Using Ontology and Semantic Understanding Capability of LLM
Pralaypati Ta, Sriram Venkatesaperumal, Keerthi Ram +1
Neuroscience research publications encompass a vast wealth of knowledge. Accurately retrieving existing information and discovering new insights from this extensive literature is e…
AAD-DCE: An Aggregated Multimodal Attention Mechanism for Early and Late Dynamic Contrast Enhanced Prostate MRI Synthesis
Divya Bharti, Sriprabha Ramanarayanan, Sadhana S +5
Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) is a medical imaging technique that plays a crucial role in the detailed visualization and identification of tissue p…
Comprehensive Modeling and Question Answering of Cancer Clinical Practice Guidelines using LLMs
Bhumika Gupta, Pralaypati Ta, Keerthi Ram +1
The updated recommendations on diagnostic procedures and treatment pathways for a medical condition are documented as graphical flows in Clinical Practice Guidelines (CPGs). For ef…
Knowledge Models for Cancer Clinical Practice Guidelines : Construction, Management and Usage in Question Answering
Pralaypati Ta, Bhumika Gupta, Arihant Jain +3
An automated knowledge modeling algorithm for Cancer Clinical Practice Guidelines (CPGs) extracts the knowledge contained in the CPG documents and transforms it into a programmatic…
Spine Vision X-Ray Image based GUI Planning of Pedicle Screws Using Enhanced YOLOv5 for Vertebrae Segmentation
Yashwanth Rao, Gaurisankar S, Durga R +4
In this paper, we propose an innovative Graphical User Interface (GUI) aimed at improving preoperative planning and intra-operative guidance for precise spinal screw placement thro…
GUI-based Pedicle Screw Planning on Fluoroscopic Images Utilizing Vertebral Segmentation
Vivek Maik, Aparna Purayath, Durga R +2
The proposed work establishes a novel Graphical User Interface (GUI) framework, primarily designed for intraoperative pedicle screw planning. Current planning workflow in Image Gui…
A Hybrid-Layered System for Image-Guided Navigation and Robot Assisted Spine Surgeries
Suhail Ansari T, Vivek Maik, Minhas Naheem +3
In response to the growing demand for precise and affordable solutions for Image-Guided Spine Surgery (IGSS), this paper presents a comprehensive development of a Robot-Assisted an…
A Hybrid-Layered System for Image-Guided Navigation and Robot Assisted Spine Surgery
Suhail Ansari T, Vivek Maik, Minhas Naheem +3
In response to the growing demand for precise and affordable solutions for Image-Guided Spine Surgery (IGSS), this paper presents a comprehensive development of a Robot-Assisted an…
Online Action Representation using Change Detection and Symbolic Programming
Vishnu S Nair, Sneha Sree, Jayaraj Joseph +1
This paper addresses the critical need for online action representation, which is essential for various applications like rehabilitation, surveillance, etc. The task can be defined…
DCE-FORMER: A Transformer-based Model With Mutual Information And Frequency-based Loss Functions For Early And Late Response Prediction In Prostate DCE-MRI
Sadhana S, Sriprabha Ramanarayanan, Arunima Sarkar +3
Dynamic Contrast Enhanced Magnetic Resonance Imaging aids in the detection and assessment of tumor aggressiveness by using a Gadolinium-based contrast agent (GBCA). However, GBCA i…
Immersive Virtual Reality Platform for Robot-Assisted Antenatal Ultrasound Scanning
Shyam A, Aparna Purayath, Keerthivasan S +4
Maternal health remains a pervasive challenge in developing and underdeveloped countries. Inadequate access to basic antenatal Ultrasound (US) examinations, limited resources such…
Geometric Learning-Based Transformer Network for Estimation of Segmentation Errors
Sneha Sree C, Mohammad Al Fahim, Keerthi Ram +1
Many segmentation networks have been proposed for 3D volumetric segmentation of tumors and organs at risk. Hospitals and clinical institutions seek to accelerate and minimize the e…
HyperCoil-Recon: A Hypernetwork-based Adaptive Coil Configuration Task Switching Network for MRI Reconstruction
Sriprabha Ramanarayanan, Mohammad Al Fahim, Rahul G. S. +3
Parallel imaging, a fast MRI technique, involves dynamic adjustments based on the configuration i.e. number, positioning, and sensitivity of the coils with respect to the anatomy u…
SDLFormer: A Sparse and Dense Locality-enhanced Transformer for Accelerated MR Image Reconstruction
Rahul G. S., Sriprabha Ramnarayanan, Mohammad Al Fahim +3
Transformers have emerged as viable alternatives to convolutional neural networks owing to their ability to learn non-local region relationships in the spatial domain. The self-att…
Automated Knowledge Modeling for Cancer Clinical Practice Guidelines
Pralaypati Ta, Bhumika Gupta, Arihant Jain +4
Clinical Practice Guidelines (CPGs) for cancer diseases evolve rapidly due to new evidence generated by active research. Currently, CPGs are primarily published in a document forma…
Generalizing Supervised Deep Learning MRI Reconstruction to Multiple and Unseen Contrasts using Meta-Learning Hypernetworks
Sriprabha Ramanarayanan, Arun Palla, Keerthi Ram +1
Meta-learning has recently been an emerging data-efficient learning technique for various medical imaging operations and has helped advance contemporary deep learning models. Furth…