Orthopedics

Automatic segmentation of vertebrae in 3D CT images using adaptive fast 3D pulse coupled neural networks.

Two systems are presented for segmentation of vertebrae in a 3D computed tomography (CT) image. The first method extracts seven features from each voxel and uses a multi-layer perceptron neural network (MLPNN) to classify the voxel as vertebrae or background. In the second method, the segmentation is completed in two steps: first, a newly developed adaptive pulse coupled neural network (APCNN) dir...

Translation of morphological and functional musculoskeletal imaging.

In an effort to develop quantitative biomarkers for degenerative joint disease and fill the void that exists for diagnosing, monitoring, and assessing the extent of whole joint degeneration, the past decade has been marked by a greatly increased role of noninvasive imaging. This coupled with recent advances in image processing and deep learning opens new possibilities for promising quantitative te...

Force feasible set prediction with artificial neural network and musculoskeletal model.

Developing tools to predict the force capabilities of the human limbs through the Force Feasible Set (FFS) may be of great interest for robotic assist...

Artificial intelligence and deep learning in ophthalmology.

Artificial intelligence (AI) based on deep learning (DL) has sparked tremendous global interest in recent years. DL has been widely adopted in image r...

Classification of acute lymphoblastic leukemia using deep learning.

Acute Leukemia is a life-threatening disease common both in children and adults that can lead to death if left untreated. Acute Lymphoblastic Leukemia...

Joint Classification and Prediction CNN Framework for Automatic Sleep Stage Classification.

Correctly identifying sleep stages is important in diagnosing and treating sleep disorders. This paper proposes a joint classification-and-prediction ...

Deep neural network improves fracture detection by clinicians.

Suspected fractures are among the most common reasons for patients to visit emergency departments (EDs), and X-ray imaging is the primary diagnostic t...

Regression Convolutional Neural Network for Automated Pediatric Bone Age Assessment From Hand Radiograph.

Skeletal bone age assessment is a common clinical practice to investigate endocrinology, and genetic and growth disorders of children. However, clinic...

Development and validation of a robotic system for ankle joint testing.

Ankle sprains are the most common sports injury. Gaining a better understanding of ankle mechanics will help improve current treatments, enabling a be...

Control of a Robot Arm Using Decoded Joint Angles from Electrocorticograms in Primate.

Electrocorticogram (ECoG) is a well-known recording method for the less invasive brain machine interface (BMI). Our previous studies have succeeded in...

Vitamin D status in relation to age, bone mineral density of the spine and femur in obese Saudi females - A hospital-based study.

The aim of the present study was to evaluate the association between Bone mineral density in lumber spine and femoral neck with serum total levels of ...

CT image segmentation of bone for medical additive manufacturing using a convolutional neural network.

BACKGROUND: The most tedious and time-consuming task in medical additive manufacturing (AM) is image segmentation. The aim of the present study was to...

3D convolutional neural networks for detection and severity staging of meniscus and PFJ cartilage morphological degenerative changes in osteoarthritis and anterior cruciate ligament subjects.

BACKGROUND: Semiquantitative assessment of MRI plays a central role in musculoskeletal research; however, in the clinical setting MRI reports often te...

Prediction of spinal curve progression in Adolescent Idiopathic Scoliosis using Random Forest regression.

BACKGROUND: The progression of the spinal curve represents one of the major concerns in the assessment of Adolescent Idiopathic Scoliosis (AIS). The p...

FRAX Calculated without BMD Resulting in a Higher Fracture Risk Than That Calculated with BMD in Women with Early Breast Cancer.

BACKGROUND AND PURPOSE: The aim of this study was to investigate the importance of including the measurement of bone mineral density (BMD) in reliable...

A study of intracortical porosity's area fractions and aspect ratios using computer vision and pulse-coupled neural networks.

Employing computer vision (CV) and optimized pulse-coupled neural networks (PCNN), this work automatically quantifies the geometrical attributes of in...

Artificial Intelligence Applied to Osteoporosis: A Performance Comparison of Machine Learning Algorithms in Predicting Fragility Fractures From MRI Data.

BACKGROUND: A current challenge in osteoporosis is identifying patients at risk of bone fracture.

Gene ontology enrichment analysis of congenital diaphragmatic hernia-associated genes.

Congenital diaphragmatic hernia (CDH) is a commonly occurring major congenital anomaly with a profound impact on neonatal mortality. The etiology of C...

-Value: A Potential Biomarker for Assessing Knee-Joint Health Using Acoustical Emission Sensing.

This paper explores the novel application of an automated -value extraction algorithm for the interpretation of sounds produced by the knee joint duri...

Registration-Based Organ Positioning and Joint Segmentation Method for Liver and Tumor Segmentation.

The automated segmentation of liver and tumor from CT images is of great importance in medical diagnoses and clinical treatment. However, accurate and...