The introduction of augmented reality: At the Oral & Maxillofacial Department of the University Medical Center Utrecht

The complexity and interdependency of hospital activities make it challenging to seamlessly integrate new technologies into clinical routines, especially with various stakeholders involved. Considering contextual factors when implementing innovations has been recognized as critical to success. This highlights the significance of an approach that...

Deep Learning-Based Automatic Detection and Classification of Rib Fractures from CT scans

Introduction: Trauma-induced rib fractures are a common injury, affecting millions of individuals globally each year. Although anteroposterior thoracic radiographs are part of the standard posttraumatic screening, the most sensitive modality, and therefore golden standard for diagnosing rib fractures, is computed tomography (CT). Still, between...

Segmentation of Deep Inferior Epigastric Artery Perforators for Breast Reconstruction using Deep Learning in Computed Tomography Angiography: A Quantitative and Qualitative Evaluation

<b>Introduction: </b>Breast reconstruction after a mastectomy is crucial to improve a patient’s quality of life. The Deep Inferior Epigastric artery Perforator (DIEP) flap procedure is considered the golden standard for breast reconstruction. Three-dimensional (3D) visualization methods have shown promise in providing a better understanding of...

Predicting the stability of distal radius fractures with a small dataset and machine learning

Purpose. Distal radius fractures are common fractures of the wrist. These fractures are often displaced and need reduction, after adequate reduction, the patients will have follow-up X-rays to check if the fracture stays stable. This is important because surgery might be required if the fracture becomes unstable. This can lead to delayed surgery...

Level localisation for lumbar surgery using ultrasound

Wrong-level spine surgery (WLS) is a medical error with severe consequences for the patient and medical staff. The current golden standard to prevent WLS during spinal surgery is fluoroscopy images acquired by a C-arm. However, this approach uses ionising radiation and interrupts the standard surgical workflow. To overcome these disadvantages,...

Outcome prediction for endovascular therapy: Multimodal deep learning for acute ischemic events in the arteria cerebri media

The efficacy of endovascular therapy in large vessel occlusion (LVO) of the anterior circulation is dependent to a high degree on the selection of patients who are likely to benefit from this procedure. To this end, functional outcome prediction based on clinical parameters is an active area of research. In the preoperative screening of LVO...

Automated functional outcome prediction in stroke using combined imaging and clinical parameters

Predicting functional outcome after intra-arterial treatment (IAT) in acute ischemic stroke (AIS) patients is an important aspect of treatment decision making and prognostics. Standard methods for functional outcome prediction after stroke combine baseline clinical (and radiological) parameters. In this study, we investigated to what extent...

Vessel Layer Separation of X-ray Angiographic Images using Deep Learning Methods

Percutaneous coronary intervention is a minimally-invasive procedure to treat coronary artery disease. In such procedures, X-ray angiography, a real-time imaging technique, is commonly used for image guidance to identify lesion sites and navigate catheters and guide-wires within coronary arteries. Due to the physical nature of X-ray imaging,...

Automatic Initialization for 3D Ultrasound CT Registration During Liver Tumor Ablations

Ablation is a medical procedure to treat liver cancer where a needle-like catheter has to be inserted into a tumor, which will then be heated or frozen to destroy the tumor tissue. To guide the catheter, Ultrasound(US) imaging is used which shows the catheter position in real time. However, some tumors are not visible on US images. To make these...