6 papers
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…
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…
Toward Generalized Image Quality Assessment: Relaxing the Perfect Reference Quality Assumption
Du Chen, Tianhe Wu, Kede Ma +1
Full-reference image quality assessment (FR-IQA) generally assumes that reference images are of perfect quality. However, this assumption is flawed due to the sensor and optical li…
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…