Latest AI and machine learning research in orthopedics for healthcare professionals.
Paleoradiology, the use of modern imaging technologies to study archaeological and anthropological remains, offers new windows on millennial scale patterns of human health. Unfortunately, the radiographs collected during field campaigns are heterogeneous: bones are disarticulated, positioning is ad hoc, and laterality markers are often absent. Additionally, factors such as age at death, age of bon...
3D human pose lifting from a single RGB image is a challenging task in 3D vision. Existing methods typically establish a direct joint-to-joint mapping from 2D to 3D poses based on 2D features. This formulation suffers from two fundamental limitations: inevitable error propagation from input predicted 2D pose to 3D predictions and inherent difficulties in handling self-occlusion cases. In this pape...
Joint-Embedding Predictive Architectures (JEPA) learn view-invariant representations and admit projection-based distribution matching for collapse pre...
Endoscopic image analysis is vital for colorectal cancer screening, yet real-world conditions often suffer from lens fogging, motion blur, and specula...
This work proposes Bonnet, an ultra-fast sparse-volume pipeline for whole-body bone segmentation from CT scans. Accurate bone segmentation is importan...
We propose VL-DUN, a principled framework for joint All-in-One Medical Image Restoration and Segmentation (AiOMIRS) that bridges the gap between low-l...
Spaceflight-associated neuro-ocular syndrome (SANS) threatens astronaut health during long-duration missions, yet its molecular pathology remains uncl...
Neurophysiologists have discovered many mechanisms underlying the production of animal behaviors in specific species; these involve a collection of ne...
Musculoskeletal disorders represent a leading cause of global disability, creating an urgent demand for precise interpretation of medical imaging. Cur...
Knee osteoarthritis (KOA) grading based on radiographic images is a critical yet challenging task due to subtle inter-grade differences, annotation un...
Brain organization is increasingly characterized through multiple imaging modalities, most notably structural connectivity (SC) and functional connect...
Federated learning enables collaborative model training across geographically distributed medical centers while preserving data privacy. However, doma...
Recent advances in medical vision language models guide the learning of visual representations; however, this form of supervision is constrained by th...
Early achievement of deep remission improves patients' outcome in chronic myeloid leukemia (CML) treatment, highlighting the need for predictive indic...
In clinical practice, medical segmentation datasets are often limited and heterogeneous, with variations in modalities, protocols, and anatomical targ...
Text-Based Person Search (TBPS) has seen significant progress with vision-language models (VLMs), yet it remains constrained by limited training data ...
Reconstructing a 3D Stereo-lithography (STL) Model from 2D Contours of scanned structure in Digital Imaging and Communication in Medicine (DICOM) imag...
Cervical spine fractures are critical medical conditions requiring precise and efficient detection for effective clinical management. This study explo...
Joint feature modeling in both the spatial and frequency domains has become a mainstream approach in MRI reconstruction. However, existing methods gen...
The human spine commonly consists of seven cervical, twelve thoracic, and five lumbar vertebrae. However, enumeration anomalies may result in individu...