2 citations · 4 across the 10 of their papers we have counts for
10 papers
Fracture Detection and Localisation in Wrist and Hand Radiographs using Detection Transformer Variants
Aditya Bagri, Vasanthakumar Venugopal, Anandakumar D +7
Background: Accurate diagnosis of wrist and hand fractures using radiographs is essential in emergency care, but manual interpretation is slow and prone to errors. Transformer-base…
A Deep Learning-Based Ensemble System for Automated Shoulder Fracture Detection in Clinical Radiographs
Hemanth Kumar M, Karthika M, Saianiruth M +8
Background: Shoulder fractures are often underdiagnosed, especially in emergency and high-volume clinical settings. Studies report up to 10% of such fractures may be missed by radi…
Autonomous AI for Multi-Pathology Detection in Chest X-Rays: A Multi-Site Study in the Indian Healthcare System
Bargava Subramanian, Shajeev Jaikumar, Praveen Shastry +6
Study Design: The study outlines the development of an autonomous AI system for chest X-ray (CXR) interpretation, trained on a vast dataset of over 5 million X rays sourced from he…
Vision-Language Models for Acute Tuberculosis Diagnosis: A Multimodal Approach Combining Imaging and Clinical Data
Ananya Ganapthy, Praveen Shastry, Naveen Kumarasami +7
Background: This study introduces a Vision-Language Model (VLM) leveraging SIGLIP and Gemma-3b architectures for automated acute tuberculosis (TB) screening. By integrating chest X…
A Multi-Site Study on AI-Driven Pathology Detection and Osteoarthritis Grading from Knee X-Ray
Bargava Subramanian, Naveen Kumarasami, Praveen Shastry +6
Introduction: Bone health disorders like osteoarthritis and osteoporosis pose major global health challenges, often leading to delayed diagnoses due to limited diagnostic tools. Th…
AI-Driven MRI Spine Pathology Detection: A Comprehensive Deep Learning Approach for Automated Diagnosis in Diverse Clinical Settings
Bargava Subramanian, Naveen Kumarasami, Praveen Shastry +7
Study Design: This study presents the development of an autonomous AI system for MRI spine pathology detection, trained on a dataset of 2 million MRI spine scans sourced from diver…
Advancing Chronic Tuberculosis Diagnostics Using Vision-Language Models: A Multi modal Framework for Precision Analysis
Praveen Shastry, Sowmya Chowdary Muthulur, Naveen Kumarasami +8
Background: This study proposes a Vision-Language Model (VLM) leveraging the SIGLIP encoder and Gemma-3b transformer decoder to enhance automated chronic tuberculosis (TB) screenin…
3D Convolutional Neural Networks for Improved Detection of Intracranial bleeding in CT Imaging
Bargava Subramanian, Naveen Kumarasami, Praveen Shastry +8
Background: Intracranial bleeding (IB) is a life-threatening condition caused by traumatic brain injuries, including epidural, subdural, subarachnoid, and intraparenchymal hemorrha…
AI and Deep Learning for Automated Segmentation and Quantitative Measurement of Spinal Structures in MRI
Praveen Shastry, Bhawana Sonawane, Kavya Mohan +9
Background: Accurate spinal structure measurement is crucial for assessing spine health and diagnosing conditions like spondylosis, disc herniation, and stenosis. Manual methods fo…
Deep Learning-Based Automated Workflow for Accurate Segmentation and Measurement of Abdominal Organs in CT Scans
Praveen Shastry, Ashok Sharma, Kavya Mohan +7
Background: Automated analysis of CT scans for abdominal organ measurement is crucial for improving diagnostic efficiency and reducing inter-observer variability. Manual segmentati…