Latest AI and machine learning research in orthopedics for healthcare professionals.
Recent diffusion-based extreme image compression methods have demonstrated remarkable performance at ultra-low bitrates. However, most approaches require training separate diffusion models for each target bitrate, resulting in substantial computational overhead and hindering practical deployment. Meanwhile, recent studies have shown that joint super-resolution can serve as an effective approach fo...
In this work, we present EchoGen, a unified framework for layout-to-image generation and image grounding, capable of generating images with accurate layouts and high fidelity to text descriptions (e.g., spatial relationships), while grounding the image robustly at the same time. We believe that image grounding possesses strong text and layout understanding abilities, which can compensate for the c...
Routine oncologic computed tomography (CT) presents an ideal opportunity for screening spinal instability, yet prophylactic stabilization windows are ...
Many wireless vision applications, such as autonomous driving, require preservation of global structural information rather than only per-pixel fideli...
Objectives Patients with osteoarthritis (OA) affecting multiple joints have poorer health outcomes than those without, yet most research examines isol...
Background: Vertebral artery calcification (VAC), a critical indicator of cerebrovascular disease, is often overlooked in head-and-neck imaging. Manua...
Background: Diffusion MRI (dMRI) is widely used to assess microstructural abnormalities in multiple sclerosis (MS), yet conventional diffusion tensor ...
Electron microscopy has enabled many scientific breakthroughs across multiple fields. A key challenge is the tuning of microscope parameters based on ...
Falls among older adults can result in hip fractures that requires x-ray based assessment at emergency department (ED). Only 25.7% of patients present...
Accurate diagnosis of glaucoma is challenging, as early-stage changes are subtle and often lack clear structural or appearance cues. Most existing app...
Existing offline feed-forward methods for joint scene understanding and reconstruction on long image streams often repeatedly perform global computati...
Collecting multiple types of data on the same set of subjects is common in modern scientific applications including, genomics, metabolomics, and neuro...
Targets supported by human genetic associations are more than twice as likely to progress from clinical development to approval. Genome-wide associati...
Large language models (LLMs) increasingly guide clinical decisions through population-level evidence, yet they cannot encode individual patient prefer...
Large language models (LLMs) are increasingly applied to financial analysis, yet their ability to audit structured financial statements under explicit...
Objective: Achilles tendon ruptures lead to long-term structural and functional deficits. Prior research that sought to identify optimal rehabilitatio...
Whole-Slide Images (WSIs) are widely used for estimating the prognosis of cancer patients. Current studies generally follow a cancer-specific learning...
Promptable Foundation Models (FMs), initially introduced for natural image segmentation, have also revolutionized medical image segmentation. The incr...
Gaussian splatting has emerged as a competitive explicit representation for image and video reconstruction. In this work, we present P-GSVC, the first...
Osteoporosis is a skeletal disease typically diagnosed using dual-energy X-ray absorptiometry (DXA), which quantifies areal bone mineral density but o...