Related papers: Anatomical Region Recognition and Real-time Bone T…
Accurate vertebra localization and identification are required in many clinical applications of spine disorder diagnosis and surgery planning. However, significant challenges are posed in this task by highly varying pathologies (such as…
This paper addresses the task of detecting and localising fetal anatomical regions in 2D ultrasound images, where only image-level labels are present at training, i.e. without any localisation or segmentation information. We examine the use…
Suture needle localization is necessary for autonomous suturing. Previous approaches in autonomous suturing often relied on fiducial markers rather than markerless detection schemes for localizing a suture needle due to the inconsistency of…
Osteoporosis is a common bone disease that occurs when the creation of new bone does not keep up with the loss of old bone, resulting in increased fracture risk. Adults over the age of 50 are especially at risk and see their quality of life…
In the realm of exoskeleton control, achieving precise control poses challenges due to the mechanical delay of exoskeletons. To address this, incorporating future gait trajectories as feed-forward input has been proposed. However, existing…
Embedded devices are omnipresent in modern networks including the ones operating inside critical environments. However, due to their constrained nature, novel mechanisms are required to provide external, and non-intrusive anomaly detection.…
The thighbone is the largest bone supporting the lower body. If the thighbone fracture is not treated in time, it will lead to lifelong inability to walk. Correct diagnosis of thighbone disease is very important in orthopedic medicine. Deep…
Automated object recognition in medical images can facilitate medical diagnosis and treatment. In this paper, we automatically segmented supraclavicular nerves in ultrasound images to assist in injecting peripheral nerve blocks. Nerve…
The aim of this study was to investigate the influence of MRI and patient data on the prediction of knee osteoarthritis (OA) incidence using different deep learning architectures. Knee OA incidence within 24 months was predicted using the…
Natural control of limb motion is continuous and progressively adaptive to individual intent. While intuitive interfaces have the potential to rely on the neuromuscular input by the user for continuous adaptation, continuous volitional…
Automatically determining the position of every slice in a CT scan is a basic yet powerful capability allowing fast retrieval of region of interest for visual inspection and automated analysis. Unlike conventional localization approaches…
Magnetic Resonance Imaging (MRI) is an essential diagnostic tool for assessing knee injuries. However, manual interpretation of MRI slices remains time-consuming and prone to inter-observer variability. This study presents a systematic…
Segmentation is a prerequisite yet challenging task for medical image analysis. In this paper, we introduce a novel deeply supervised active learning approach for finger bones segmentation. The proposed architecture is fine-tuned in an…
Various imaging artifacts, low signal-to-noise ratio, and bone surfaces appearing several millimeters in thickness have hindered the success of ultrasound (US) guided computer assisted orthopedic surgery procedures. In this work, a…
Automated segmentation of anatomical sub-regions with high precision has become a necessity to enable the quantification and characterization of cells/ tissues in histology images. Currently, a machine learning model to analyze…
Segmenting both bone surface and the corresponding acoustic shadow are fundamental tasks in ultrasound (US) guided orthopedic procedures. However, these tasks are challenging due to minimal and blurred bone surface response in US images,…
Ultrasound examination for detecting fractures is ideally suited for Emergency Departments (ED) as it is relatively fast, safe (from ionizing radiation), has dynamic imaging capability and is easily portable. High interobserver variability…
Classification and regression employing a simple Deep Neural Network (DNN) are investigated to perform touch localization on a tactile surface using ultrasonic guided waves. A robotic finger first simulates the touch action and captures the…
The use of Augmented Reality (AR) devices for surgical guidance has gained increasing traction in the medical field. Traditional registration methods often rely on external fiducial markers to achieve high accuracy and real-time…
Purpose: Accurate estimation of the position and orientation (pose) of surgical instruments is crucial for delicate minimally invasive temporal bone surgery. Current techniques lack in accuracy and/or line-of-sight constraints (conventional…