Orthopedics

Enhancing Contrastive Learning Inspired by the Philosophy of "The Blind Men and the Elephant"

Contrastive learning is a prevalent technique in self-supervised vision representation learning, typically generating positive pairs by applying two data augmentations to the same image. Designing effective data augmentation strategies is crucial for the success of contrastive learning. Inspired by the story of the blind men and the elephant, we introduce JointCrop and JointBlur. These methods g...

Using matrix-product states for time-series machine learning

Matrix-product states (MPS) have proven to be a versatile ansatz for modeling quantum many-body physics. For many applications, and particularly in one-dimension, they capture relevant quantum correlations in many-body wavefunctions while remaining tractable to store and manipulate on a classical computer. This has motivated researchers to also apply the MPS ansatz to machine learning (ML) probl...

BS-LDM: Effective Bone Suppression in High-Resolution Chest X-Ray Images with Conditional Latent Diffusion Models

Lung diseases represent a significant global health challenge, with Chest X-Ray (CXR) being a key diagnostic tool due to their accessibility and aff...

[Identification of osteoid and chondroid matrix mineralization in primary bone tumors using a deep learning fusion model based on CT and clinical features: a multi-center retrospective study].

METHODS: We retrospectively collected CT scan data from 276 patients with pathologically confirmed primary bone tumors from 4 medical centers in Guang...

Decade of Natural Language Processing in Chronic Pain: A Systematic Review

In recent years, the intersection of Natural Language Processing (NLP) and public health has opened innovative pathways for investigating various do...

Successive optimization of optics and post-processing with differentiable coherent PSF operator and field information

Recently, the joint design of optical systems and downstream algorithms is showing significant potential. However, existing rays-described methods a...

Navigating limitations with precision: A fine-grained ensemble approach to wrist pathology recognition on a limited x-ray dataset

The exploration of automated wrist fracture recognition has gained considerable research attention in recent years. In practical medical scenarios, ...

A Systematic Analysis of Input Modalities for Fracture Classification of the Paediatric Wrist

Fractures, particularly in the distal forearm, are among the most common injuries in children and adolescents, with approximately 800 000 cases trea...

FlexPose: Pose Distribution Adaptation with Limited Guidance

Numerous well-annotated human key-point datasets are publicly available to date. However, annotating human poses for newly collected images is still...

Measurement of Medial Elbow Joint Space using Landmark Detection

Ultrasound imaging of the medial elbow is crucial for the early diagnosis of Ulnar Collateral Ligament (UCL) injuries. Specifically, measuring the e...

Energy-Constrained Information Storage on Memristive Devices in the Presence of Resistive Drift

In this paper, we examine the problem of information storage on memristors affected by resistive drift noise under energy constraints. We introduce ...

VinTAGe: Joint Video and Text Conditioning for Holistic Audio Generation

Recent advances in audio generation have focused on text-to-audio (T2A) and video-to-audio (V2A) tasks. However, T2A or V2A methods cannot generate ...

Versatile Locomotion Skills for Hexapod Robots

Hexapod robots are potentially suitable for carrying out tasks in cluttered environments since they are stable, compact, and light weight. They also...

Temporomandibular joint and masticatory muscles morphometry and morphology in healthy subjects and individuals with temporomandibular dysfunction: An anatomical, radiological, and machine learning application study.

The study aimed to compare the morphometric and morphologic analyses of the bone structures of temporomandibular joint and masticatory muscles on Cone...

Computer-Aided Osteoporosis Diagnosis Using Transfer Learning with Enhanced Features from Stacked Deep Learning Modules

Knee osteoporosis weakens the bone tissue in the knee joint, increasing fracture risk. Early detection through X-ray images enables timely intervent...

Motif Guided Graph Transformer with Combinatorial Skeleton Prototype Learning for Skeleton-Based Person Re-Identification

Person re-identification (re-ID) via 3D skeleton data is a challenging task with significant value in many scenarios. Existing skeleton-based method...

Towards Precision in Bolted Joint Design: A Preliminary Machine Learning-Based Parameter Prediction

Bolted joints are critical in engineering for maintaining structural integrity and reliability. Accurate prediction of parameters influencing their ...

Adversarial Contrastive Domain-Generative Learning for Bacteria Raman Spectrum Joint Denoising and Cross-Domain Identification

Raman spectroscopy, as a label-free detection technology, has been widely utilized in the clinical diagnosis of pathogenic bacteria. However, Raman ...

Intelligent Control of Robotic X-ray Devices using a Language-promptable Digital Twin

Natural language offers a convenient, flexible interface for controlling robotic C-arm X-ray systems, making advanced functionality and controls acc...

STIV: Scalable Text and Image Conditioned Video Generation

The field of video generation has made remarkable advancements, yet there remains a pressing need for a clear, systematic recipe that can guide the ...